James Aimone

Suma George Cardwell, Catherine Schuman, John Darby Smith, Karan Patel, Jaesuk Kwon, Samuel Liu, Christopher Richard Allemang, Shashank Misra, JeanAnne Incorvia, James Bradley Aimone, (2022). Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation IEEE International Conference on Rebooting Computing Document ID: 1688071

Suma George Cardwell, Catherine Schuman, John Darby Smith, Karan Patel, Jaesuk Kwon, Samuel Liu, Christopher Richard Allemang, Shashank Misra, JeanAnne Incorvia, James Bradley Aimone, (2022). Probabilistic Neural Circuits leveraging AI-Enhanced Codesign for Random Number Generation IEEE International Conference on Rebooting Computing Document ID: 1677283

James Bradley Aimone, (2022). Computing with Noisy Neurons Gage Lab Symposium Document ID: 1675580

James Bradley Aimone, (2022). A Probabilistic Future for Neuromorphic Computing Invited talk at UCSD Document ID: 1675586

James Bradley Aimone, (2022). A Probabilistic Future for Neuromorphic Computing Sandia Loves Science Document ID: 1664423

Samuel Liu, Jaesuk Kwon, PaulW. Bessler, Suma George Cardwell, Catherine Schuman, John Darby Smith, Shashank Misra, James Bradley Aimone, JeanAnne Incorvia, (2022). Design and evaluation of efficient random bit-streams using spin orbit torque and voltage-controlled magnetic anisotropy in magnetic tunnel junctions Iedm Document ID: 1664318

Bradley Harold Theilman, Felix Wang, James Bradley Aimone, (2022). Identifying Recurrent Causal Activity Patterns in Spiking Neural Networks CRCNS PI Meeting 2022 Document ID: 1663782

Shashank Misra, Christopher Richard Allemang, Laura Rehm, AndrewD. Kent, JeanAnne Incorvia, Les Bland, Suma George Cardwell, John Darby Smith, James Bradley Aimone, (2022). Probabilistic computing and device stochasticity APS March Meeting 2023 Document ID: 1653550

Craig Michael Vineyard, James Bradley Aimone, Abrar Anwar, Ryan Anthony Dellana, Esteban J. Guillen, Mark Plagge, William Mark Severa, Javier Zazueta, Andrew Sornborger, Diegochavez Arana, Oleksandr Iaroshenko, Gerd Kunde, Alpha Renner, Anatoly Zlotnik, (2022). SEEK: Scoping neuromorphic architecture impact enabling advanced sensing capabilities https://www.osti.gov/search/identifier:1891944 Document ID: 1652533

Bradley Harold Theilman, Yipu Wang, Ojas D. Parekh, William Mark Severa, John Darby Smith, James Bradley Aimone, (2022). Stochastic Neuromorphic Circuits for Finding Graph Max Cuts IEEE International Parallel and Distributed Processing Symposium Document ID: 1641555

Bradley Harold Theilman, James Bradley Aimone, (2022). Neuromorphic circuits for generating useful correlations from random bit streams SIAM Conference on Computational Science and Engineering Minisymposium on Probabilistic Computing Document ID: 1641261

James Bradley Aimone, (2022). A Probabilistic Future for Neuromorphic Computing CINT User Meeting Document ID: 1630529

Bradley Harold Theilman, Felix Wang, James Bradley Aimone, (2022). Identifying Recurrent Causal Activity Patterns in Spiking Neural Networks CRCNS PI Meeting Document ID: 1630383

James Bradley Aimone, Prasanna Date, Gabriel Fonseca-Guerra, Kathleen Hamilton, Kyle Henke, Bill Kay, Garrett Kenyon, Shruti Kulkarni, Maryam Parsa, Catherine Schuman, William Mark Severa, John Darby Smith, (2022). A Review of Non-Cognitive Applications for Neuromorphic Computing IOP Science Neuromorphic Computing and Engineering https://www.osti.gov/search/identifier:1887407 Document ID: 1618675

James Bradley Aimone, (2022). Overview and Opportunities for Neuromorphic Computing SFI WorkshopThermodynamics of Natural and Artificial Computation Document ID: 1606931

Shashank Misra, Leslie Bland, Suma George Cardwell, JA Incorvia, Conrad D. James, Andy Kent, Catherine Schuman, John Darby Smith, James Bradley Aimone, (2022). Probabilistic Neural Computing with Stochastic Devices Advanced Materials Document ID: 1606566

William Mark Severa, John Darby Smith, Richard B. Lehoucq, James Bradley Aimone, (2022). Learning to Parameterize a Stochastic Processing Using Neuromorphic Data Generation International Conference on Neuromorphic Systems Document ID: 1584897

James Bradley Aimone, Suma George Cardwell, Frances S. Chance, Srideep Musuvathy, Fredrick Rothganger, William Mark Severa, John Darby Smith, Corinne Michelle Teeter, Craig Michael Vineyard, Felix Wang, (2022). Neural Mini-Apps: Lighter, Faster Diagnostic Tests for Neuromorphic Computing Document ID: 1573711

Felix Wang, Corinne Michelle Teeter, Sarah Katherine Luca, Srideep Musuvathy, James Bradley Aimone, (2022). Distributed Localization with Grid-based Representations on Digital Elevation Models International Conference on Neuromorphic Systems Document ID: 1574658

William Mark Severa, John Darby Smith, Richard B. Lehoucq, James Bradley Aimone, (2022). Learning to Parameterize a Stochastic Process Using Neuromorphic Data Generation International Conference on Neuromorphic Systems Document ID: 1574459

Felix Wang, Corinne Michelle Teeter, Sarah Katherine Luca, Srideep Musuvathy, James Bradley Aimone, (2022). Distributed Localization with Grid-based Representations on Digital Elevation Models International Conference on Neuromorphic Systems Document ID: 1574258

James Bradley Aimone, (2022). Evaluating the Potential of Neuromorphic Computing for Scientific Computing Applications 2022 ASC PI Meeting Document ID: 1528331

James Bradley Aimone, (2022). COINFLIPS: CO-designed Improved Neural Foundations Leveraging Inherent Physics Stochasticity 2022 NICE Conference Document ID: 1493481

Craig Michael Vineyard, James Bradley Aimone, Ryan Anthony Dellana, Esteban J. Guillen, Aaron Jamison Hill, William Mark Severa, Javier Zazueta, (2022). Spiking Neural Approaches to SAR ATR SPIE Defense and Commercial Sensing Document ID: 1493680

Felix Wang, Corinne Michelle Teeter, Sarah Katherine Luca, Srideep Musuvathy, James Bradley Aimone, (2022). Localization through Grid-based Encodings on Digital Elevation Models Neuro-Inspired Computational Elements Workshop Document ID: 1493265

James Bradley Aimone, Jean Anne Incorvia, (2022). COINFLIPS: CO-designed Improved Neural Foundations Leveraging Inherent Physics Stochasticity UT Austin Sandia Day Document ID: 1493330

Craig Michael Vineyard, James Bradley Aimone, Suma George Cardwell, Frances S. Chance, Srideep Musuvathy, Fredrick Rothganger, John Darby Smith, William Mark Severa, Corinne Michelle Teeter, Felix Wang, (2022). Neural Mini-Apps as a Tool for Neuromorphic Computing Insight Neuro-Inspired Computational Elements (NICE) Workshop 2022 Document ID: 1493378

Craig Michael Vineyard, Suma George Cardwell, Frances S. Chance, Srideep Musuvathy, Fredrick Rothganger, William Mark Severa, John Darby Smith, Corinne Michelle Teeter, Felix Wang, James Bradley Aimone, (2022). Neural Mini-Apps as a Tool for Neuromorphic Computing Insight The 9th Annual Neuro-Inspired Computational Elements (NICE) workshop Document ID: 1470530

Felix Wang, Corinne Michelle Teeter, Sarah Katherine Luca, Srideep Musuvathy, James Bradley Aimone, (2022). Localization through Grid-based Encodings on Digital Elevation Models Neuro-Inspired Computational Elements Workshop Document ID: 1459850

John Darby Smith, Aaron Jamison Hill, Reeder Leah, Brian C. Franke, Richard B. Lehoucq, Ojas D. Parekh, William Mark Severa, James Bradley Aimone, (2022). Neuromorphic scaling advantages for energy-efficient random walk computations Nature Electronics https://www.osti.gov/search/identifier:1845387 Document ID: 1427616

James Bradley Aimone, (2022). Recipes and tools for neuromorphic computing Lab Research Technical Exchange Document ID: 1427486

James Bradley Aimone, (2022). Neural Plasticity, Computation, and Three Reasons We May be Stuck DARPA MEC Workshop Document ID: 1426954

John Darby Smith, Richard B. Lehoucq, James Bradley Aimone, William Mark Severa, (2021). Assessing a Neuromorphic Platform for use in Scientific Stochastic Sampling International Conference on Rebooting Computing Document ID: 1404118

Ojas D. Parekh, Yipu Wang, Yang Ho, Cynthia Ann Phillips, Ali Pinar, James Bradley Aimone, William Mark Severa, (2021). Neuromorphic Graph Algorithms https://www.osti.gov/search/identifier:1829422 Document ID: 1391697

John Darby Smith, James Bradley Aimone, William Mark Severa, Richard B. Lehoucq, (2021). Assessing a Neuromorphic Platform for use in Scientific Stochastic Sampling International Conference on Rebooting Computing Document ID: 1392326

James Bradley Aimone, Aaron Jamison Hill, William Mark Severa, Craig Michael Vineyard, (2021). Spiking Neural Streaming Binary Arithmetic IEEE International Conference on Rebooting Computing (ICRC 2021) Document ID: 1370828

James Bradley Aimone, Alexander Mikhailovich Safonov, (2021). Mapping Stochastic Devices to Probabilistic Algorithms https://www.osti.gov/search/identifier:1821523 Document ID: 1367404

James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang, (2021). Provable Advantages for Graph Algorithms in Spiking Neural Networks ACM Symposium on Parallelism in Algorithms and Architectures Document ID: 1319287

James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang, (2021). Provable advantages for graph algorithms in spiking neural networks 33rd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2021) https://www.osti.gov/search/identifier:1871422 Document ID: 1307449

Christopher Bennett, Ryan Anthony Dellana, Tianyao Xiao, Benjamin Feinberg, Sapan Agarwal, Suma George Cardwell, Matthew Marinella, William Mark Severa, James Bradley Aimone, (2021). Evaluating complexity and resilience trade-offs in emerging memory inference machines NICE Virtual Conference Proceedings https://www.osti.gov/search/identifier:1859699 Document ID: 1281557

William Mark Severa, James Bradley Aimone, Craig Michael Vineyard, Srideep Musuvathy, Yang Ho, Zubin Alexander Kane, Leah Reeder, (2021). Platform-Agnostic Neural Algorithm Composition using Fugu Neuro-Inspired Computational Elements https://www.osti.gov/search/identifier:1856292 Document ID: 1281554

James Bradley Aimone, (2021). A Neuromorphic Future for Classic Computing Tasks 2021 Neuro Inspired Computational Elements Conference https://www.osti.gov/search/identifier:1855320 Document ID: 1281018

John Darby Smith, William Mark Severa, Richard B. Lehoucq, James Bradley Aimone, (2021). Learning to Solve an Inverse Problem Using Neuromorphic Data Generation Smoky Mountains Conference Document ID: 1280890

James Bradley Aimone, (2021). Scaling up Markov Chain Monte Carlo on Loihi Intel INRC Winter Meeting 2021 https://www.osti.gov/search/identifier:1848044 Document ID: 1268352

James Bradley Aimone, (2020). A roadmap for reaching the potential of brain-derived computing Advanced Intelligent Systems https://www.osti.gov/search/identifier:1760460 Document ID: 1209220

James Bradley Aimone, (2020). Preparing for the Next Generation of Brain-Inspired AI ValleyML https://www.osti.gov/search/identifier:1826436 Document ID: 1209325

James Bradley Aimone, Christopher Bennett, Suma George Cardwell, Ryan Anthony Dellana, Tianyao Xiao, (2020). Mosaic, The Best of Both Worlds: Analog devices with Digital Spiking Communication to build a Hybrid Neural Network Accelerator https://www.osti.gov/search/identifier:1673175 Document ID: 1208242

John Darby Smith, Aaron Jamison Hill, Leah Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas D. Parekh, William Mark Severa, James Bradley Aimone, (2020). Neuromorphic scaling advantages for energy-efficient random walk computations https://www.osti.gov/search/identifier:1671377 Document ID: 1207930

Suma George Cardwell, James Bradley Aimone, (2020). Truly heterogeneous HPC: Co-design to achieve what science needs from HPC Smoky Mountains Computational Sciences & Engineering Conference https://www.osti.gov/search/identifier:1818046 Document ID: 1195358

James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang, (2020). Brief Announcement: Provable neuromorphic advantages for computing constrained shortest paths 32nd ACM Symposium on Parallelism in Algorithms and Architectures https://www.osti.gov/search/identifier:1814114 Document ID: 1162052

John Darby Smith, William Mark Severa, Aaron Jamison Hill, Leah Reeder, Ojas D. Parekh, Brian C. Franke, Richard B. Lehoucq, James Bradley Aimone, (2020). Solving a steady-state pde using spiking networks and neuromorphic hardware International Conference on Neuromorphic Systems https://www.osti.gov/search/identifier:1813714 Document ID: 1184356

John Darby Smith, William Mark Severa, Aaron Jamison Hill, Leah Evelyn Reeder, Brian C. Franke, Richard B. Lehoucq, Ojas D. Parekh, James Bradley Aimone, (2020). Solving a steady-state pde using spiking networks and neuromorphic hardware International Conference on Neuromorphic Systems https://www.osti.gov/search/identifier:1808426 Document ID: 1161991

James Bradley Aimone, Yang Ho, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Yipu Wang, (2020). Brief Announcement: Provable neuromorphic advantages for computing constrained shortest paths 32nd ACM Symposium on Parallelism in Algorithms and Architectures (SPAA 2020) https://www.osti.gov/search/identifier:1808434 Document ID: 1138751

James Bradley Aimone, (2020). A Neuromorphic Future for Classic Computing Problems 2020 NICE Workshop Document ID: 1091444

James Bradley Aimone, (2020). A Neuromorphic Future for Classic Computing Tasks Intel INRC Forum https://www.osti.gov/search/identifier:1785161 Document ID: 1127622

Frances S. Chance, James Bradley Aimone, Srideep Musuvathy, Michael Reed Smith, Craig Michael Vineyard, Felix Wang, (2020). Crossing the Cleft: Communication Challenges Between Neuroscience and Artificial Intelligence Frontiers in Computational Neuroscience https://www.osti.gov/search/identifier:1617318 Document ID: 1116284

Suma George Cardwell, James Bradley Aimone, Craig Michael Vineyard, William Mark Severa, Frances S. Chance, (2020). Truly heterogeneous HPC: co-design to achieve what science needs from HPC Smoky Mountains Computational Sciences & Engineering Conference Document ID: 1115949

Craig Michael Vineyard, James Bradley Aimone, William Mark Severa, Mark Plagge, Thomas A. Reichardt, Andrew Sornborger, (2020). SEEK – Scoping neuromorphic architecture impact enabling advanced sensing capabilities Nuclear Security Applications Research & Development (NSARD) https://www.osti.gov/search/identifier:1772874 Document ID: 1114897

Christopher Bennett, Ryan Anthony Dellana, Tianyao Xiao, Benjamin Feinberg, Sapan Agarwal, Suma George Cardwell, Matthew Marinella, William Mark Severa, James Bradley Aimone, (2020). Evaluating complexity and resilience trade-offs in emerging memory inference machines 2020 Neuro-Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1768142 Document ID: 1092852

John Darby Smith, James Bradley Aimone, William Mark Severa, (2020). Leveraging Random Walks to Solve IPDEs on Spiking Neuromorphic Hardware SIAM Parallel Processing https://www.osti.gov/search/identifier:1765110 Document ID: 1091520

John Darby Smith, James Bradley Aimone, Brian C. Franke, Aaron Jamison Hill, Richard B. Lehoucq, Ojas D. Parekh, Leah Evelyn Reeder, William Mark Severa, (2020). Solving IPDEs on Spiking Neuromorphic Hardware Joint Math Meetings https://www.osti.gov/search/identifier:1761032 Document ID: 1079000

John Darby Smith, James Bradley Aimone, (2019). Leveraging Random Walks and Neuromorphic Hardware to Solve Elliptical Integro-PDEs SIAM Parallel Processing Document ID: 1067452

Leah Evelyn Reeder, James Bradley Aimone, William Mark Severa, (2019). The Future of Computing: Integrating Scientific Computation on Neuromorphic Systems https://www.osti.gov/search/identifier:1592947 Document ID: 1066890

Suma George Cardwell, Christopher Bennett, James Bradley Aimone, Ryan Anthony Dellana, Sapan Aggarwal, (2019). Evaluating complexity and resilience trade-offs in emerging memory inference machines Neuro-Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1643292 Document ID: 1056082

James Bradley Aimone, (2019). Preparing for the Next Generation of AI UT San Antonio AI Summit https://www.osti.gov/search/identifier:1643272 Document ID: 1055527

James Bradley Aimone, (2019). Computing with Spikes SRC Decadal Planning Workshop https://www.osti.gov/search/identifier:1646089 Document ID: 1033455

Felix Wang, William Mark Severa, James Bradley Aimone, (2019). Context-modulation of hippocampal dynamics and deep convolutional networks Neuroscience 2019 https://www.osti.gov/search/identifier:1642866 Document ID: 1033817

Suma George Cardwell, James Bradley Aimone, Christopher Bennett, Ryan Anthony Dellana, Suma George Cardwell, William Mark Severa, (2019). Mosaics, a technique to make neuromorphic computing scalable, adaptive and flexible International Conference on Artificial Intelligence Circuits and Systems https://www.osti.gov/search/identifier:1642761 Document ID: 1032879

Srideep Musuvathy, James Bradley Aimone, Suma George Cardwell, Frances S. Chance, Ryan Anthony Dellana, Yang Ho, Leah Evelyn Reeder, William Mark Severa, Craig Michael Vineyard, Felix Wang, (2019). Fugu: Algorithm Development for Neuromorphic Hardware Intel Neuromorphic Research Community Fall Workshop https://www.osti.gov/search/identifier:1646072 Document ID: 1032818

Felix Wang, James Bradley Aimone, Srideep Musuvathy, Abrar Anwar, (2019). BrainSLAM https://www.osti.gov/search/identifier:1569159 Document ID: 1031385

James Bradley Aimone, William Mark Severa, Craig Michael Vineyard, (2019). Composing Neural Algorithms with Fugu Icons https://www.osti.gov/search/identifier:1641992 Document ID: 996510

James Bradley Aimone, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Helen Xu, (2019). Dynamic Programming with Spiking Neural Computing International Conference on Neuromorphic Systems https://www.osti.gov/search/identifier:1641666 Document ID: 996846

Aaron Jamison Hill, Jonathon W. Donaldson, Fredrick H. Rothganger, Craig Michael Vineyard, David R. Follett, Pamela L. Follett, Michael Reed Smith, Stephen Joseph Verzi, William Mark Severa, Felix Wang, James Bradley Aimone, John H. Naegle, Conrad D. James, (2019). Neuromorphic Computing Algorithms and Architecture Research at Sandia Ccd Titans Intern Tech Talk https://www.osti.gov/search/identifier:1645676 Document ID: 997001

James Bradley Aimone, Ojas D. Parekh, Cynthia Ann Phillips, Ali Pinar, William Mark Severa, Helen Xu, (2019). Dynamic Programming with Spiking Neural Computing International Conference of Neuromorphic Systems (ICONS) 2019 https://www.osti.gov/search/identifier:1641311 Document ID: 996589

James Bradley Aimone, William Mark Severa, Craig Michael Vineyard, (2019). Whetstone R&D 100 Submission Document ID: 961108

James Bradley Aimone, (2019). Mosaics 2019 NICE Workshop https://www.osti.gov/search/identifier:1639878 Document ID: 947549

James Bradley Aimone, (2019). Computing as a Constraint to Understand the Hippocampus Seminar at UC Irvine CNLM https://www.osti.gov/search/identifier:1648762 Document ID: 959736

Craig Michael Vineyard, Ryan Anthony Dellana, James Bradley Aimone, William Mark Severa, (2019). Low-Power Deep Learning Inference using the SpiNNaker Neuromorphic Platform Nice 2019 https://www.osti.gov/search/identifier:1639535 Document ID: 947681

Aaron Jamison Hill, William Mark Severa, Craig Michael Vineyard, Ryan Anthony Dellana, Leah Evelyn Reeder, Felix Wang, James Bradley Aimone, Angel Yanguas-Gil, (2019). Building a Comprehensive Neuromorphic Platform for Remote Computation GOMACTech https://www.osti.gov/search/identifier:1639487 Document ID: 937320

Leah Evelyn Reeder, James Bradley Aimone, William Mark Severa, Aaron Jamison Hill, (2019). Applications of Random Walks Utilizing Neuromorphic Computing Neuro Inspired Computational Elements Workshop (NICE) https://www.osti.gov/search/identifier:1639488 Document ID: 937338

Sam Green, James Bradley Aimone, (2019). Neuromorphic Computing: Memristors Learn to Play Nature Electronics https://www.osti.gov/search/identifier:1575274 Document ID: 936503

Craig Michael Vineyard, Ryan Anthony Dellana, James Bradley Aimone, William Mark Severa, (2019). Low-Power Deep Learning Inference using the SpiNNaker Neuromorphic Platform https://www.osti.gov/search/identifier:1761866 Document ID: 936170

William Mark Severa, Aaron Jamison Hill, Craig Michael Vineyard, Ryan Anthony Dellana, Leah Evelyn Reeder, Felix Wang, James Bradley Aimone, Angel Yanguas-Gil, (2019). Building a Comprehensive Neuromorphic Platform for Remote Computation Gomactech https://www.osti.gov/search/identifier:1592219 Document ID: 902302

Tu-Thach Quach, Sapan Agarwal, Conrad D. James, Matthew Marinella, James Bradley Aimone, (2018). Sparse Data Acquisition on Emerging Memory Architectures IEEE Access https://www.osti.gov/search/identifier:1492354 Document ID: 901041

James Bradley Aimone, (2018). Computing as a Constraint to Understand the Brain: A Case Study in Neural Plasticity University of Utah Neuroscience Snowbird Symposium https://www.osti.gov/search/identifier:1806995 Document ID: 877476

James Bradley Aimone, Kathleen E Hamilton, Susan Mniszewski, Leah Evelyn Reeder, Catherine D. Schuman, William Mark Severa, (2018). Non-Neural Network Applications for Spiking Neuromorphic Hardware Post-Moore’s Era Supercomputing (Workshop for Supercomputing 2018) Document ID: 877389

James Bradley Aimone, (2018). Novel approaches to numerical computing using neural algorithms UNM Applied Mathematics Seminar https://www.osti.gov/search/identifier:1806954 Document ID: 876551

Michael Reed Smith, Joey Burton Ingram, Christopher Lamb, Timothy J. Draelos, Justin E Doak, James Bradley Aimone, Conrad D. James, (2018). Dynamic Analysis of Executables to Detect and Characterize Malware IEEE International Conference on Machine Learning and Applications (IEEE ICMLA) https://www.osti.gov/search/identifier:1806881 Document ID: 865656

Aleksandra Faust, James Bradley Aimone, Conrad D. James, Lydia Tapia, (2018). Resilient Computing with Reinforcement Learning on a Dynamical System: Case Study in Sorting IEEE Conference on Decision and Control https://www.osti.gov/search/identifier:1592260 Document ID: 865306

James Bradley Aimone, Aaron Jamison Hill, Richard B. Lehoucq, Ojas D. Parekh, Leah Evelyn Reeder, William Mark Severa, (2018). Neural Algorithms for Low Power Implementation of Partial Differential Equations https://www.osti.gov/search/identifier:1474253 Document ID: 865530

Leah Evelyn Reeder, Aaron Jamison Hill, James Bradley Aimone, William Mark Severa, (2018). Exploring Applications of Random Walks on Spiking Neural Algorithms https://www.osti.gov/search/identifier:1471656 Document ID: 855111

Craig Michael Vineyard, William Mark Severa, Ryan Anthony Dellana, Leah Evelyn Reeder, Felix Wang, James Bradley Aimone, Angel Yanguas-Gil, (2018). Building a Comprehensive Neuromorphic Platform for Remote Computation GOMAC Tech 2019 Document ID: 855065

James Bradley Aimone, Aaron Jamison Hill, Richard B. Lehoucq, Ojas D. Parekh, William Mark Severa, (2018). Neuromorphic Hardware Implementation of Spiking Algorithms for Markov Random Walks 2018 International Conference on Neuromorphic Systems (ICONS) https://www.osti.gov/search/identifier:1582258 Document ID: 831045

William Mark Severa, Craig Michael Vineyard, Ryan Anthony Dellana, Stephen Joseph Verzi, James Bradley Aimone, (2018). Whetstone: A Method for Training Deep Artificial Neural Networks for Binary Communication Arxiv Document ID: 853404

Stephen Joseph Verzi, Fredrick Rothganger, Ojas D. Parekh, Tu-Thach Quach, Nadine E. Miner, Craig Michael Vineyard, Conrad D. James, James Bradley Aimone, (2018). Computing with Spikes: The Advantage of Fine-grained Timing Neural Computation https://www.osti.gov/search/identifier:1466763 Document ID: 842920

James Bradley Aimone, (2018). Neural Algorithms and Machine Learning Beyond Moore’s Law Sandia ML / DL 2018 https://www.osti.gov/search/identifier:1574260 Document ID: 841910

William Mark Severa, Craig Michael Vineyard, Ryan Anthony Dellana, James Bradley Aimone, (2018). Whetstone: An Accessible, Platform-Independent Method for Training Spiking Deep Neural Networks for Neuromorphic Processors International Conference on Neuromorphic Systems (ICONS) 2018 https://www.osti.gov/search/identifier:1806670 Document ID: 831239

William Mark Severa, Ryan Anthony Dellana, Craig Michael Vineyard, James Bradley Aimone, (2018). Whetstone: An accessible, platform-independent method training spiking deep neural networks for neuromorphic processors International Conference on Neuromorphic Systems https://www.osti.gov/search/identifier:1806636 Document ID: 831086

Stephen Joseph Verzi, Craig Michael Vineyard, James Bradley Aimone, (2018). Neural-inspired Anomaly Detection The Ninth International Conference on Complex Systems (ICCS) 2018 https://www.osti.gov/search/identifier:1570938 Document ID: 830703

Tu-Thach Quach, Sapan Agarwal, Conrad D. James, Matthew Marinella, James Bradley Aimone, (2018). Sparse Data Acquisition on Emerging Memory Architectures https://www.osti.gov/search/identifier:1530151 Document ID: 830613

William Mark Severa, Richard B. Lehoucq, Ojas D. Parekh, James Bradley Aimone, (2018). Spiking Neural Algorithms for Markov Process Random Walk International Joint Conference on Neural Networks https://www.osti.gov/search/identifier:1532605 Document ID: 819905

Stephen Joseph Verzi, Craig Michael Vineyard, James Bradley Aimone, (2018). Neural-Inspired Anomaly Detection The Ninth International Conference on Complex Systems (ICCS) 2018 https://www.osti.gov/search/identifier:1524953 Document ID: 807988

Ojas D. Parekh, Cynthia Ann Phillips, Conrad D. James, James Bradley Aimone, (2018). Constant-Depth and Subcubic-Size Threshold Circuits for Matrix Multiplication 30th ACM Symposium on Parallelism in Algorithms and Architectures https://www.osti.gov/search/identifier:1523356 Document ID: 807519

William Mark Severa, Richard B. Lehoucq, Ojas D. Parekh, James Bradley Aimone, (2018). Spiking Neural Algorithms for Markov Process Random Walk International Joint Conference on Neural Networks 2018 https://www.osti.gov/search/identifier:1525633 Document ID: 795559

Felix Wang, Tu-Thach Quach, Jason W. Wheeler, James Bradley Aimone, Conrad D. James, (2018). Sparse Coding for N-Gram Feature Extraction and Training for File Fragment Classification IEEE Transactions on Information Forensics and Security https://www.osti.gov/search/identifier:1432478 Document ID: 783444

James Bradley Aimone, (2018). A direct application of neuromorphic computing to numerical computing Neuro-inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1500150 Document ID: 761318

William Mark Severa, Craig Michael Vineyard, Ryan Anthony Dellana, James Bradley Aimone, (2018). Whetstone: An Accessible, Platform-Independent Method for Training Spiking Deep Neural Networks for Neuromorphic Processors NICE Workshop https://www.osti.gov/search/identifier:1498219 Document ID: 761354

Craig Michael Vineyard, Stephen Joseph Verzi, William Mark Severa, James Bradley Aimone, (2018). Spiking Neuron Implementations of Several Fundamental Machine Learning Algorithms Neural Inspired Computational Elements Workshop 2018 https://www.osti.gov/search/identifier:1498201 Document ID: 761328

William Mark Severa, Ryan Anthony Dellana, Craig Michael Vineyard, James Bradley Aimone, (2018). Whetstone: An accessible, platform-independent method for training spiking deep neural networks for neuromorphic processors SysML 2018 https://www.osti.gov/search/identifier:1572444 Document ID: 760645

James Bradley Aimone, William Mark Severa, (2018). Context-modulation of hippocampal dynamics and deep convolutional networks Nips https://www.osti.gov/search/identifier:1513733 Document ID: 727188

William Mark Severa, Craig Michael Vineyard, Ryan Anthony Dellana, James Bradley Aimone, (2018). Whetstone: An accessible, platform-independent method for training spiking deep neural networks for neuromorphic processors SysML Conference 2018 Document ID: 739369

Justin E Doak, Joey Burton Ingram, Samuel A. Mulder, John H. Naegle, Jonathan A. Cox, James Bradley Aimone, Kevin R. Dixon, Conrad D. James, David R. Follett, (2017). Tracking Cyber Adversaries with Adaptive Indicators of Compromise 4th Annual Conf. on Computational Science & Computational Intelligence; THE 2017 INTERNATIONAL SYMPOSIUM ON CYBER WARFARE, CYBER DEFENSE, AND SECURITY https://www.osti.gov/search/identifier:1486988 Document ID: 727483

James Bradley Aimone, William Mark Severa, (2017). Context-modulation of hippocampal dynamics and deep convolutional networks NIPS Workshop on Cognitively Informed AI https://www.osti.gov/search/identifier:1484567 Document ID: 726030

James Bradley Aimone, Ojas D. Parekh, William Mark Severa, (2017). Neural Computing for Scientific Computing Applications Neuromorphic Computing – Architectures – Models – Applications https://www.osti.gov/search/identifier:1483116 Document ID: 726074

Justin E Doak, Justin E Doak, Joey Burton Ingram, Joey Burton Ingram, Samuel A. Mulder, Samuel A. Mulder, John H. Naegle, John H. Naegle, Jonathan A. Cox, Jonathan A. Cox, James Bradley Aimone, James Bradley Aimone, Kevin R. Dixon, Kevin R. Dixon, Conrad D. James, Conrad D. James, David R. Follet, David R. Follet, (2017). Tracking Cyber Adversaries with Adaptive Indicators of Compromise 4th Annual Conf. on Computational Science & Computational Intelligence; THE 2017 INTERNATIONAL SYMPOSIUM ON CYBER WARFARE, CYBER DEFENSE, AND SECURITY https://www.osti.gov/search/identifier:1511128 Document ID: 725925

Aaron Jamison Hill, William Mark Severa, James Bradley Aimone, (2017). TrueNorth Implementation of a Temporally Coded Spiking Cross-Correlation Algorithm for Particle Image Velocimetry International Conference on Rebooting Computing https://www.osti.gov/search/identifier:1480592 Document ID: 725011

William Mark Severa, Jerilyn A. Timlin, Suraj Kholwadwala, Conrad D. James, James Bradley Aimone, (2017). Data-driven Feature Sampling for Deep Hyperspectral Classification and Segmentation IEEE Signal Processing in Medicine and Biology Symposium https://www.osti.gov/search/identifier:1509662 Document ID: 671824

Aaron Jamison Hill, Jonathon W. Donaldson, Fredrick Rothganger, Craig Michael Vineyard, David R. Follett, Pamela L. Follett, Michael Reed Smith, Stephen Joseph Verzi, William Mark Severa, Felix Wang, James Bradley Aimone, John H. Naegle, Conrad D. James, (2017). A Spike-Timing Neuromorphic Architecture IEEE International Conference on Rebooting Computing (ICRC 2017) https://www.osti.gov/search/identifier:1470698 Document ID: 671325

James Bradley Aimone, (2017). Hardware Acceleration of Adaptive Neural Algorithms Sandia Computing and Information Sciences External Review Board https://www.osti.gov/search/identifier:1508727 Document ID: 670371

John H. Naegle, Roger A. Suppona, James Bradley Aimone, Conrad D. James, David R. Follett, Duncan C.M. Townsend, Pamela L. Follett, Gabe D. Karpman, (2017). Neuromorphic Data Microscope ACM Journal of Emerging Technologies https://www.osti.gov/search/identifier:1478335 Document ID: 659943

Frances S. Chance, James Bradley Aimone, Kristofor Carlson, Warren Leon Davis, Jacob Aaron Hobbs, Timothy Malcolm Shead, Stephen Joseph Verzi, Craig Michael Vineyard, (2017). Keeping the brain in brain-inspired computing: Test and Evaluation for MICrONS Sandia CIS Review Board Document ID: 659846

Stephen Joseph Verzi, Ryan Anthony Dellana, William Mark Severa, Michael Reed Smith, Fredrick Rothganger, Conrad D. James, James Bradley Aimone, Craig Michael Vineyard, (2017). Steep Deep Spiking Networks Sandia Machine Learning/Deep Learning (MLDL) Conference https://www.osti.gov/search/identifier:1464724 Document ID: 659568

Timothy J. Draelos, Nadine E. Miner, Jonathan Cox, Christopher Lamb, Craig Michael Vineyard, Kristofor Carlson, William Mark Severa, Conrad D. James, James Bradley Aimone, (2017). Neurogenesis Deep Learning Academic Alliance Faculty Field Day Poster Session https://www.osti.gov/search/identifier:1462930 Document ID: 658930

James Bradley Aimone, William Mark Severa, Ojas D. Parekh, (2017). Neural Computing for Scientific Computing Applications: Neuromorphic ComputingArchitectures – Models – Applications Workshop https://www.osti.gov/search/identifier:1507953 Document ID: 637981

William Mark Severa, Aaron Jamison Hill, Conrad D. James, James Bradley Aimone, (2017). Hardware Spike Timing for Accelerating Computational Algorithms IEEE International Conference on Rebooting Computing Document ID: 625032

Nicholas Soures, Abdullah M. A. Zyarah, Kristofor David Carlson, James Bradley Aimone, Dhireesha Kudithipudi, (2017). How Neural Plasticity Boosts Performance of Spiking Neural Networks Annual Conference on Cognitive Computational Neuroscience https://www.osti.gov/search/identifier:1458069 Document ID: 624364

Craig Michael Vineyard, Ojas D. Parekh, Cynthia Ann Phillips, James Bradley Aimone, Conrad D. James, Craig Michael Vineyard, Craig Michael Vineyard, (2017). Adaptive Learning Theory Poster display in Neural Exploration and Research Lab https://www.osti.gov/search/identifier:1367220 Document ID: 624369

Timothy J. Draelos, Nadine E. Miner, Christopher Lamb, Jonathan cox, Craig Michael Vineyard, Kristofor David Carlson, William Mark Severa, Conrad D. James, James Bradley Aimone, (2017). Neurogenesis Deep Learning: Extending deep Networks to accommodate new classes IEEE International Joint Conference on Neural Networks https://www.osti.gov/search/identifier:1457976 Document ID: 624161

Meghan Anne Sahakian, Stephen Joseph Verzi, Craig Michael Vineyard, Eric D. Vugrin, Conrad D. James, James Bradley Aimone, (2017). Optimization-based computation with spiking neurons International Joint Conference on Neural Networks https://www.osti.gov/search/identifier:1457893 Document ID: 623760

Michael Reed Smith, Aaron Jamison Hill, Kristofor David Carlson, Craig Michael Vineyard, Jonathon W. Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James Bradley Aimone, (2017). A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to LSMs The 2017 International Joint Conference on Neural Networks (IJCNN 2017) https://www.osti.gov/search/identifier:1457873 Document ID: 623403

James Bradley Aimone, (2017). The Computing World is Ready for Brain Inspiration ? But what will be the Biggest Impact? R&D Magazine https://www.osti.gov/search/identifier:1429769 Document ID: 611396

James Bradley Aimone, (2017). Exponential scaling of neural algorithms ? a future beyond Moore?s Law? biorxiv https://www.osti.gov/search/identifier:1429770 Document ID: 599940

John H. Naegle, Roger A. Suppona, James Bradley Aimone, Conrad D. James, David R. (LRL) Follett, Duncan C. M. (LRL) Townsend, Gabe D. (LRL) Karpman, (2017). Hot Chips 2017 Abstract: Neuromorphic Data Microscope Hot Chips 29 (2017) Document ID: 611218

Tu-Thach Quach, Sapan Agarwal, Conrad D. James, Matthew Marinella, James Bradley Aimone, (2017). Efficient Memory Acquisition via Sparse Sampling Non-Volatile Memories Workshop 2017 https://www.osti.gov/search/identifier:1429259 Document ID: 600462

Michael Reed Smith, Aaron Jamison Hill, Kristofor David Carlson, Craig Michael Vineyard, Jonathon W. Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James Bradley Aimone, (2017). An Efficient Implementation of a Liquid State Machine on the Spiking Temporal Processing Unit Neuro Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1427932 Document ID: 599724

Michael Reed Smith, Aaron Jamison Hill, Kristofor David Carlson, Craig Michael Vineyard, Jonathon W. Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James Bradley Aimone, Michael Reed Smith, Michael Reed Smith, (2017). An Efficient Implementation of a LSM on the Spiking Temporal Processing Unit Neuro Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1427931 Document ID: 599806

Ojas D. Parekh, Cynthia Ann Phillips, Meghan Anne Sahakian, Conrad D. James, James Bradley Aimone, (2017). Constant Depth and Subcubic Size Threshold Circuits for Matrix Multiplication 5th Neuro Inspired Computational Elements Workshop (NICE 2017) https://www.osti.gov/search/identifier:1425316 Document ID: 599825

James Bradley Aimone, (2017). Hippocampus-Inspired Adaptive Neural Algorithms Neuro Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1424871 Document ID: 599688

Timothy J. Draelos, Nadine E. Miner, Christopher Lamb, Jonathan A. Cox, Craig Michael Vineyard, Kristofor David Carlson, William Mark Severa, Conrad D. James, James Bradley Aimone, (2017). Neurogenesis Deep Learning Ijcnn 2-17 https://www.osti.gov/search/identifier:1424868 Document ID: 599720

Stephen Joseph Verzi, Craig Michael Vineyard, Eric D. Vugrin, Meghan Anne Sahakian, Conrad D. James, James Bradley Aimone, (2017). Optimization-based Computation with Spiking Neurons International Joint Conference on Neural Networks (IJCNN) 2017 https://www.osti.gov/search/identifier:1431555 Document ID: 589077

James Bradley Aimone, (2017). Hippocampus-inspired Adaptive Neural Algorithms NICE Workshop Document ID: 578270

Tu-Thach Quach, Sapan Agarwal, Conrad D. James, Matthew Marinella, James Bradley Aimone, (2017). Efficient Memory Acquisition via Sparse Sampling Non-Volatile Memory Workshop https://www.osti.gov/search/identifier:1427095 Document ID: 577772

Cynthia Ann Phillips, Ojas D. Parekh, Craig Michael Vineyard, Conrad D. James, James Bradley Aimone, (2017). Studying Adaptive Learning through Game-Theoretic Modeling Neuro Inspired Computational Elements Workshop Document ID: 566740

Craig Michael Vineyard, Cynthia Ann Phillips, Ojas D. Parekh, Craig Michael Vineyard, Conrad D. James, James Bradley Aimone, (2017). Studying Adaptive Learning through Game-Theoretic Modeling Neuro Inspired Computational Elements Workshop Document ID: 566605

Conrad D. James, James Bradley Aimone, Nadine E. Miner, Craig Michael Vineyard, Fredrick Rothganger, Kristofor David Carlson, Samuel A. Mulder, Timothy J. Draelos, Aleksandra Faust, Matthew Marinella, John H. Naegle, Steven J. Plimpton, (2016). A historical survey of algorithms and hardware architectures for neural-inspired and neuromorphic computing applications Biologically Inspired Cognitive Architectures https://www.osti.gov/search/identifier:1340263 Document ID: 565218

Timothy J. Draelos, Nadine E. Miner, Christopher Lamb, Craig Michael Vineyard, Kristofor David Carlson, Conrad D. James, James Bradley Aimone, (2016). Neurogenesis Deep Learning https://www.osti.gov/search/identifier:1505351 Document ID: 565745

James Bradley Aimone, (2016). DOE National Laboratories and BRAIN: Neural Computing at Sandia National Laboratories BRAIN Initiative Investigators Meeting https://www.osti.gov/search/identifier:1413582 Document ID: 565537

William Mark Severa, Kristofor David Carlson, Ojas D. Parekh, Craig Michael Vineyard, James Bradley Aimone, (2016). Can we be formal in assessing the strengths and weaknesses of neural architectures? A case study using a spiking cross-correlation algorithm Neural Information Processing Systems https://www.osti.gov/search/identifier:1413431 Document ID: 565029

Stephen Joseph Verzi, Craig Michael Vineyard, Eric D. Vugrin, Meghan Anne Sahakian, Conrad D. James, James Bradley Aimone, (2016). Optimization-based computation with spiking neurons NIPS workshop on Computing with Spikes https://www.osti.gov/search/identifier:1422128 Document ID: 564891

Stephen Joseph Verzi, Craig Michael Vineyard, Eric D. Vugrin, Meghan Anne Sahakian, Conrad D. James, James Bradley Aimone, (2016). Optimization-based computation with spiking neurons NIPS 2016 workshop on Computing with Spikes https://www.osti.gov/search/identifier:1422129 Document ID: 564892

William Mark Severa, Kristofor David Carlson, Ojas D. Parekh, Craig Michael Vineyard, James Bradley Aimone, (2016). Can we be formal in assessing the strengths and weaknesses of neural architectures? A case study using a spiking cross-correlation algorithm Neural Information Processing Systems (NIPS) 2016 – Computing with Spikes Workshop Document ID: 554511

William Mark Severa, Kristofor David Carlson, Ojas D. Parekh, Craig Michael Vineyard, James Bradley Aimone, (2016). Can we be formal in assessing the strengths and weaknesses of neural architectures? A case study using a spiking cross-correlation algorithm Neural Information Processing Systems (NIPS) 2016 https://www.osti.gov/search/identifier:1410236 Document ID: 554568

Craig Michael Vineyard, James Bradley Aimone, Stephen Joseph Verzi, Jonathon W. Donaldson, Michael Reed Smith, Fredrick Rothganger, David R. Follet, Conrad D. James, John H. Naegle, (2016). A neurally inspired spiking temporal processing unit computational architecture Society for Neuroscience 2016 https://www.osti.gov/search/identifier:1526843 Document ID: 553820

Kristofor David Carlson, James Bradley Aimone, (2016). Applying Uncertainty Quantification and Sensitivity Analysis to Spiking Neural Network Models of Asynchronous Irregular Firing Activity Society for Neurosciene Annual Meeting 2016 https://www.osti.gov/search/identifier:1408952 Document ID: 553921

James Bradley Aimone, (2016). What are new neurons good for: both in your brain and on your cell phone? 2016 Gage Lab Symposium https://www.osti.gov/search/identifier:1408948 Document ID: 553726

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2016). Formalizing Function within the Hippocampal Trisynaptic Circuit Society for Neuroscience 2016 https://www.osti.gov/search/identifier:1408291 Document ID: 553704

KE Bouchard, James Bradley Aimone, M Chun, Dean T, M Denker, M Diesmann, DD Donofrio, LM Frank, N Kasthuri, Koch C, O Ruebel, HD Simon, FT Sommer, Prabhat, (2016). High Performance Computing in Neuroscience for Data-driven Discovery, Integration, and Dissemination Neuron https://www.osti.gov/search/identifier:1332918 Document ID: 552771

Michael Reed Smith, Aaron Jamison Hill, Kristofor David Carlson, Craig Michael Vineyard, Jonathon W. Donaldson, David R. Follett, Pamela L. Follett, John H. Naegle, Conrad D. James, James Bradley Aimone, (2016). Implementation of a Liquid State Machine with Temporal Dynamics on a Novel Spiking Neuromorphic Architecture Workshop on Neuromorphic Computing and Algorithms, WI-BIH’16 https://www.osti.gov/search/identifier:1405258 Document ID: 531961

Fredrick Rothganger, James Bradley Aimone, Conrad D. James, (2016). Computing with Dynamical Systems IEEE Conference on Rebooting Computing https://www.osti.gov/search/identifier:1404805 Document ID: 531973

William Mark Severa, Ojas D. Parekh, Kristofor David Carlson, Conrad D. James, James Bradley Aimone, (2016). Spiking Network Algorithms for Scientific Computing IEEE International Conference on Rebooting Computing (ICRC 2016) https://www.osti.gov/search/identifier:1401930 Document ID: 531888

Conrad D. James, William Mark Severa, Timothy J. Draelos, James Bradley Aimone, Craig Michael Vineyard, Sapan Agarwal, Alexander W Hsia, David Russell Hughart, Patrick Sean Finnegan, Robin B Jacobs-Gedrim, Elliot James Fuller, Albert Alec Talin, Matthew Marinella, Richard Schiek, Steven J. Plimpton, (2016). Neural machine learning algorithms and hardware for image analysis and data science applications 2016 International Conference on Brain Informatics and Health, International Workshop on Neuromorphic Computing and Algorithms https://www.osti.gov/search/identifier:1398356 Document ID: 530850

James Bradley Aimone, (2016). Revisiting the Canonical Model of the Hippocampus UNM Neuroscience Seminar Series https://www.osti.gov/search/identifier:1529815 Document ID: 528693

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2016). A Combinatorial Model for Dentate Gyrus Sparse Coding Neural Computation https://www.osti.gov/search/identifier:1371475 Document ID: 507761

Huiyun Du, Wei Deng, James Bradley Aimone, Minyan Ge, Sarah Parylak, Keenan Walch, Jonathan Cook, Wei Zhang, Huina Song, Liping Wang, Fred H Gage, Yangling Mu, (2016). Dopaminergic Inputs in the Dentate Gyrus Direct the Choice of Memory Encoding Proceedings of the National Academy of Sciences https://www.osti.gov/search/identifier:1328121 Document ID: 475479

William Mark Severa, Ojas D. Parekh, Kristofor David Carlson, Conrad D. James, James Bradley Aimone, (2016). Spiking Network Algorithms for Scientific Computing IEEE International Conference on Rebooting Computing (ICRC 2016) https://www.osti.gov/search/identifier:1373236 Document ID: 476320

Matthew Marinella, Sapan Agarwal, Steven J. Plimpton, Albert Alec Talin, Farid El Gabaly Marquez, Elliot James Fuller, David Russell Hughart, Ojas D. Parekh, Erik Debenedictis, Ronald S. Goeke, Alexander W Hsia, James Bradley Aimone, Conrad D. James, (2016). Emerging Technologies for the Acceleration of Neuromorphic Algorithms The Ninth Workshop on Fault-Tolerant Spaceborne Computing Employing New Technologies, 2016 https://www.osti.gov/search/identifier:1505271 Document ID: 464238

James Bradley Aimone, Kristofor David Carlson, Fredrick Rothganger, (2016). Neural Computing: What Scale and Complexity is Needed? Neuromorphic Computing Workshop https://www.osti.gov/search/identifier:1367782 Document ID: 475477

Kristofor David Carlson, James Bradley Aimone, (2016). Applying uncertainty quantification and sensitivity analysis to spiking neural network models of asynchronous irregular firing activity Society for Neuroscience Annual Conference 2016 Document ID: 442798

Craig Michael Vineyard, James Bradley Aimone, Michael Reed Smith, Stephen Joseph Verzi, Gabriel ANUOLUWAPO Popoola, Felix Wang, Jonathon W. Donaldson, Pamela Follett, David Follett, Conrad D. James, John H. Naegle, (2016). A neurally inspired spiking temporal processing unit computational architecture Society for Neuroscience 2016 meeting Document ID: 442944

Craig Michael Vineyard, James Bradley Aimone, Michael Reed Smith, Stephen Joseph Verzi, Gabriel ANUOLUWAPO Popoola, Felix Wang, Jonathon W. Donaldson, Pamela Follett, David Follett, Conrad D. James, John H. Naegle, (2016). A neurally inspired spiking temporal processing unit architecture Society for Neuroscience 2016 meeting Document ID: 442796

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2016). Formalizing Function within the Hippocampal Trisynaptic Circuit Society for Neuroscience (Neuroscience) 2016 Document ID: 442809

Kristofor David Carlson, James Bradley Aimone, Fredrick Rothganger, (2016). Computational Perspectives on Adult Neurogenesis Rewiring the BrainA Computational Approach to Structural Plasticity in the Adult Brain https://www.osti.gov/search/identifier:1574646 Document ID: 431976

Timothy J. Draelos, Nadine E. Miner, Jonathan Albert Cox, Christopher Lamb, William Mark Severa, Conrad D. James, James Bradley Aimone, (2016). Neurogenic Deep Learning International Conference on Learning Representations https://www.osti.gov/search/identifier:1365357 Document ID: 442492

Matthew Marinella, Sapan Agarwal, David Russell Hughart, Steven J. Plimpton, Ojas D. Parekh, Tu-Thach Quach, Erik Debenedictis, Ronald S. Goeke, Alexander W Hsia, James Bradley Aimone, Conrad D. James, (2016). Acceleration of Neural Algorithms using Nanoelectronic Resistive Memory Crossbars IEEE Rebooting Computing Symposium 4 https://www.osti.gov/search/identifier:1365322 Document ID: 365658

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2016). Spiking Network Algorithms for Scientific Computing IEEE International Conference on Rebooting Computing Document ID: 442284

Craig Michael Vineyard, Stephen Joseph Verzi, Conrad D. James, James Bradley Aimone, (2016). Quantifying Neural Information Content: A Case Study of the Impact of Hippocampal Adult Neurogenesis IEEE World Congress on Computational Intelligence 2016 https://www.osti.gov/search/identifier:1365153 Document ID: 431672

James Bradley Aimone, Kristofor David Carlson, Fredrick Rothganger, (2016). Neural Computing: What Scale and Complexity is Needed? Oak Ridge Neuromorphic Computing Workshop Document ID: 431173

Christina V Dieni, Roberto Panichi, James Bradley Aimone, Chay T Kuo, Jacques I Wadiche, Linda Overstreet-Wadiche, (2016). Low Excitatory Innervation Balances High Intrinsic Excitability Nature Communications https://www.osti.gov/search/identifier:1249080 Document ID: 430198

Sapan Agarwal, Ojas D. Parekh, Tu-Thach Quach, Erik Debenedictis, Conrad D. James, Matthew Marinella, James Bradley Aimone, (2016). Energy Scaling Advantages of Resistive Memory Crossbar Based Computation Neuro Inspired Computational Elements https://www.osti.gov/search/identifier:1422171 Document ID: 409372

Craig Michael Vineyard, Stephen Joseph Verzi, Conrad D. James, James Bradley Aimone, (2016). Quantifying neural information content: a case study of the impact of hippocampal adult neurogenesis https://www.osti.gov/search/identifier:1561002 Document ID: 409206

James Bradley Aimone, (2016). Modulating Neural Computation NICE Workshop https://www.osti.gov/search/identifier:1346463 Document ID: 409282

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2016). A Combinatorial Model of Dentate Gyrus Sparse Coding and Pattern Separation NICE Workshop https://www.osti.gov/search/identifier:1346453 Document ID: 409286

Sapan Agarwal, Steven J. Plimpton, Ojas D. Parekh, Alexander W Hsia, Tu-Thach Quach, David Russell Hughart, Isaac Richter, Erik Debenedictis, Conrad D. James, James Bradley Aimone, Matthew Marinella, (2016). Acceleration of Neural Algorithms using Nanoelectronic Resistive Memory Crossbars Neuro Inspired Computational Elements https://www.osti.gov/search/identifier:1346466 Document ID: 409288

Kristofor David Carlson, James Bradley Aimone, (2016). Applying Uncertainty Quantification and Sensitivity Analysis to Large-Scale Hippocampal Brain Models 2016 Neuro-Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1345886 Document ID: 409102

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2016). A Combinatorial Model of Dentate Gyrus Sparse Coding and Pattern Separation NICE Workshop https://www.osti.gov/search/identifier:1345889 Document ID: 408997

Timothy J. Draelos, Nadine E. Miner, Jonathan Albert Cox, Christopher Lamb, Conrad D. James, James Bradley Aimone, (2016). Neurogenic Deep Learning Internation Conference on Learning Representations https://www.osti.gov/search/identifier:1344833 Document ID: 398453

Frances S. Chance, James Bradley Aimone, Kristofor David Carlson, Warren Leon Davis, Timothy Malcolm Shead, Craig Michael Vineyard, (2016). Sandia MICrONS Phase 1 kickoff slides Machine Intelligence from Cortical Networks (MICrONS) Program Kickoff https://www.osti.gov/search/identifier:1514321 Document ID: 386851

James Bradley Aimone, Ojas D. Parekh, William Mark Severa, (2015). A Sparse Coding Model of the Hippocampal Dentate Gyrus 2016 Joint Mathematics Meetings https://www.osti.gov/search/identifier:1337917 Document ID: 376108

Erik Debenedictis, Fredrick Rothganger, James Bradley Aimone, Matthew Marinella, Brian Robert Evans, Christina E. Warrender, Patrick Mickel, (2015). Cognitive Computing for Security https://www.osti.gov/search/identifier:1234812 Document ID: 341715

Craig Michael Vineyard, James Bradley Aimone, Michael Lewis Bernard, Kristofor David Carlson, Frances S. Chance, James C. Forsythe, Conrad D. James, Fredrick Rothganger, William Mark Severa, Ann Speed, Stephen Joseph Verzi, Christina E. Warrender, John S. Wagner, Leann Adams Miller, (2015). Neural Computing at Sandia National Laboratories Rebooting Computing Summit (RCS 4) https://www.osti.gov/search/identifier:1335732 Document ID: 365383

Matthew Marinella, Sapan Agarwal, David Russell Hughart, Steven J. Plimpton, Ojas D. Parekh, Tu-Thach Quach, Erik Debenedictis, Ronald S. Goeke, Alexander W Hsia, James Bradley Aimone, Conrad D. James, (2015). Acceleration of Neural Algorithms using Nanoelectronic Resistive Memory Crossbars IEEE Rebooting Computing Symposium 4 https://www.osti.gov/search/identifier:1336275 Document ID: 365302

Kristofor David Carlson, James Bradley Aimone, (2015). Applying uncertainty quantification and sensitivity analysis to large-scale hippocampal brain models The 9th Annual Postdoctoral Technical Showcase https://www.osti.gov/search/identifier:1338026 Document ID: 365072

Kristofor David Carlson, James Bradley Aimone, (2015). Applying uncertainty quantification and sensitivity analysis to large-scale hippocampal brain models The 9th Annual Postdoctoral Technical Showcase Document ID: 364873

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2015). Finding Triangles and Tracking Particles: Using Spiking Neural Networks for Pattern Identification Algorithms The 9th Annual Postdoctoral Technical Showcase https://www.osti.gov/search/identifier:1333797 Document ID: 364945

Matthew Marinella, Sapan Agarwal, David Russell Hughart, Steven J. Plimpton, Ojas D. Parekh, Tu-Thach Quach, Erik Debenedictis, Ronald S. Goeke, Patrick Sean Finnegan, Rudeger H.T. Wilke, Denis Mamaluy, Harold P. Hjalmarson, Brian David Tierney, Alexander W Hsia, James Bradley Aimone, Conrad D. James, (2015). Acceleration of Neural Algorithms using Nanoelectronic Resistive Memory Crossbars IEEE Rebooting Computing Symposium 4 Document ID: 364990

William Mark Severa, Ojas D. Parekh, Conrad D. James, James Bradley Aimone, (2015). Finding Triangles and Tracking Particles: Using Spiking Neural Networks for Pattern Identification Algorithms The 9th Annual Postdoctoral Technical Showcase Document ID: 354758

Conrad D. James, James Bradley Aimone, (2015). A signal processing approach for cyber data classification with deep neural networks Complex Adaptive Systems https://www.osti.gov/search/identifier:1333250 Document ID: 354057

William Mark Severa, Ojas D. Parekh, James Bradley Aimone, (2015). A Combinatorial Model for Dentate Gyrus Sparse Coding and Pattern Separation Computational and Systems Neuroscience (Cosyne) 2016 Document ID: 354681

Sapan Agarwal, Ojas D. Parekh, Tu-Thach Quach, Erik Debenedictis, Conrad D. James, Matthew Marinella, James Bradley Aimone, (2015). Energy Scaling Advantages of Resistive Memory Crossbar Based Computation and its Application to Sparse Coding Neuro-Inspired Computational Elements Workshop Document ID: 354625

Kristofor David Carlson, James Bradley Aimone, (2015). Applying Uncertainty Quantification and Sensitivity Analysis to a Large-Scale Neural Model of Neurogenesis in the Dentate Gyrus Computational and Systems Neuroscience (Cosyne) 2016 Document ID: 354537

Sapan Agarwal, Tu-Thach Quach, Ojas D. Parekh, Erik Debenedictis, Conrad D. James, Matthew Marinella, James Bradley Aimone, (2015). Energy Scaling Advantages of Resistive Memory Crossbar Based Computation and its Application to Sparse Coding Frontiers in Neuroscience https://www.osti.gov/search/identifier:1236485 Document ID: 343176

Fredrick Rothganger, David Follett, John H. Naegle, Felix Wang, Jonathon W. Donaldson, Craig Michael Vineyard, Conrad D. James, James Bradley Aimone, (2015). Neural circuit models on emulated hardware Society for Neuroscience Annual Meeting 2015 https://www.osti.gov/search/identifier:1332881 Document ID: 343005

James Bradley Aimone, Conrad D. James, Christina E. Warrender, (2015). Dimensionality reduction of cortical spiking networks ? quantifying the structure behind the chaos Society for Neuroscience Annual Meeting https://www.osti.gov/search/identifier:1530663 Document ID: 342664

Craig Michael Vineyard, Stephen Joseph Verzi, Conrad D. James, James Bradley Aimone, (2015). Quantifying neural information content: A case study of the impact of hippocampal adult neurogenesis through computational modeling Neurosience 2015 https://www.osti.gov/search/identifier:1336353 Document ID: 342760

Sapan Agarwal, Ojas D. Parekh, Tu-Thach Quach, Conrad D. James, James Bradley Aimone, Matthew Marinella, (2015). The Energy Scaling Advantages of RRAM Crossbars Fourth Berkeley Symposium on Energy Efficient Electronic Systems https://www.osti.gov/search/identifier:1327962 Document ID: 342339

William Mark Severa, James Bradley Aimone, Ojas D. Parekh, (2015). A Sparse Coding Model of the Hippocampal Dentate Gyrus 2016 Joint Mathematics Meetings Document ID: 321554

Craig Michael Vineyard, Stephen Joseph Verzi, Conrad D. James, James Bradley Aimone, Gregory Heileman, (2015). Repeated Play of the SVM Game as a Means of Adaptive Classification 2015 International Joint Conference on Neural Networks https://www.osti.gov/search/identifier:1301966 Document ID: 308113

Sapan Agarwal, Ojas D. Parekh, Tu-Thach Quach, Conrad D. James, James Bradley Aimone, Matthew Marinella, (2015). The Energy Scaling Advantages of RRAM Crossbars Fourth Berkeley Symposium on Energy Efficient Electronic Systems https://www.osti.gov/search/identifier:1261043 Document ID: 307428

Fredrick Rothganger, Brian Robert Evans, James Bradley Aimone, Erik Debenedictis, (2015). Training neural hardware with noisy components International Joint Conference on Neural Networks https://www.osti.gov/search/identifier:1257569 Document ID: 286635

Craig Michael Vineyard, Stephen Joseph Verzi, Conrad D. James, James Bradley Aimone, Gregory L Heileman, (2015). MapReduce SVM Game 2015 INNS Conference on Big Data https://www.osti.gov/search/identifier:1256556 Document ID: 286523

James Bradley Aimone, Christina E. Warrender, Conrad D. James, (2015). Dimensionality reduction of cortical spiking networks ? quantifying the structure behind the chaos Society for Neuroscience Annual Meeting Document ID: 265315

Fredrick Rothganger, James Bradley Aimone, (2015). Pattern Classification using Dynamic Networks Society for Neuroscience Annual Meeting 2015 Document ID: 265383

Craig Michael Vineyard, Stephen Joseph Verzi, Conrad D. James, James Bradley Aimone, (2015). Quantifying neural information content: a case study of the impact of hippocampal adult neurogenesis through computational modeling Society for Neuroscience 2015 Annual Meeting Document ID: 265395

Fredrick Rothganger, Brian Robert Evans, James Bradley Aimone, Erik Debenedictis, (2015). Training neural hardware with noisy components International Joint Conference on Neural Networks https://www.osti.gov/search/identifier:1249470 Document ID: 264558

Conrad D. James, James Bradley Aimone, John H. Naegle, Steven J. Plimpton, Matthew Marinella, Justin E Doak, David (Lewis Rhodes Labs) Follett, (2015). Hardware Acceleration of Adaptive Neural Algorithms (HAANA) Internal Sandia Labs Seminar – Dean Seminar Document ID: 264704

Craig Michael Vineyard, Stephen Joseph Verzi, James Bradley Aimone, Conrad D. James, Gregory L. Heileman, (2015). Repeated Play of the SVM Game as a Means of Adaptive Classification 2015 International Joint Conference on Neural Networks https://www.osti.gov/search/identifier:1249447 Document ID: 264716

Conrad D. James, James Bradley Aimone, Steven J. Plimpton, John H. Naegle, Matthew Marinella, Kevin R. Dixon, David (Lewis Rhodes Labs) Follett, (2015). Hardware Acceleration of Adaptive Neural Algorithms (HAANA) Internal Sandia Labs Seminar – Dean Seminar https://www.osti.gov/search/identifier:1249448 Document ID: 264694

James Bradley Aimone, (2015). Computational Modeling of Adult Neurogenesis Neurogenesis https://www.osti.gov/search/identifier:1202792 Document ID: 254210

Matthew Marinella, Sapan Agarwal, David Russell Hughart, Patrick R. Mickel, Alexander W Hsia, Steven J. Plimpton, Seth Decker, Roger Apodaca, James Bradley Aimone, Conrad D. James, Timothy J. Draelos, (2015). Resistive Memory for Neuromorphic Algorithm Acceleration Neural Inspired Computing Elements Document ID: 243610

James Bradley Aimone, Rita Betty, (2015). Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation/Completion of Episodic Information https://www.osti.gov/search/identifier:1172176 Document ID: 232038

Matthew Marinella, Sapan Agarwal, David Russell Hughart, Patrick R. Mickel, Alexander W Hsia, Steven J. Plimpton, Seth Decker, Roger Apodaca, James Bradley Aimone, Conrad D. James, Timothy J. Draelos, (2015). Resistive Memory for Neuromorphic Algorithm Acceleration Neural Inspired Computing Elements https://www.osti.gov/search/identifier:1240257 Document ID: 221957

Fredrick Rothganger, Brian Robert Evans, James Bradley Aimone, Erik Debenedictis, (2015). Can memristors learn? 2015 Neuro-Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1240117 Document ID: 221843

James Bradley Aimone, (2015). Adaptive Neural Algorithms: The What, Why, and How Neural Inspired Computational Elements Workshop https://www.osti.gov/search/identifier:1504363 Document ID: 221653

Fredrick Rothganger, Conrad D. James, Kevin R. Dixon, James Bradley Aimone, (2015). Biologically-Inspired Computing at Sandia Northrop-Grumman Biologically-Inspired Computing Workshop https://www.osti.gov/search/identifier:1237876 Document ID: 220652

Erik Debenedictis, James Bradley Aimone, (2014). Review of "Cross Neural" Research Effort Ad hoc meeting https://www.osti.gov/search/identifier:1242706 Document ID: 218726

Fredrick Rothganger, Derek Trumbo, Christina E. Warrender, James Bradley Aimone, (2014). How to model the whole brain? Society for Neuroscience Annual Meeting 2014 https://www.osti.gov/search/identifier:1315167 Document ID: 208464

Stephen Joseph Verzi, James Bradley Aimone, (2014). Quantification of Neural Computation 2014 Annual International Conference on Biologically Inspired Cognitive Architectures https://www.osti.gov/search/identifier:1315443 Document ID: 208025

James Bradley Aimone, Michael Lewis Bernard, Craig Michael Vineyard, Stephen Joseph Verzi, (2014). Using High Performance Computing to Examine the Processes of Neurogenesis Underlying Pattern Separation and Completion of Episodic Information https://www.osti.gov/search/identifier:1162373 Document ID: 176867

Matthew Marinella, Patrick R. Mickel, Andrew Lohn, David Russell Hughart, Robert James Bondi, Denis Mamaluy, Harold P. Hjalmarson, James E. Stevens, Seth Decker, Roger Apodaca, Brian Robert Evans, James Bradley Aimone, Fredrick Rothganger, Conrad D. James, Erik Debenedictis, (2014). Development, Characterization, and Modeling of a TaOx ReRAM for a Neuromorphic Accelerator https://www.osti.gov/search/identifier:1241888 Document ID: 166432

Matthew Marinella, Patrick R. Mickel, Andrew Lohn, David Russell Hughart, Robert James Bondi, Denis Mamaluy, Harold P. Hjalmarson, James E. Stevens, Seth Decker, Roger Apodaca, Brian Robert Evans, James Bradley Aimone, Fredrick Rothganger, Conrad D. James, Erik Debenedictis, (2014). Development, Characterization, and Modeling of a TaOx ReRAM for a Neuromorphic Accelerator 226th Meeting of the Electrochemical Society https://www.osti.gov/search/identifier:1241770 Document ID: 112468

Craig Michael Vineyard, Stephen Joseph Verzi, James Bradley Aimone, (2014). Quantification of Neural Computation 2014 Annual International Conference on Biologically Inspired Cognitive Architectures Document ID: 166130

Patrick R. Mickel, James Bradley Aimone, Matthew Marinella, (2013). Memristors as Synapses in Artificial Neural Networks: Biomimicry Beyond Weight Change https://www.osti.gov/search/identifier:1675279 Document ID: 5330758

Stephen Joseph Verzi, Michael Lewis Bernard, James Bradley Aimone, Thomas P. Caudell, (2013). Adult Neurogenesis: Implications on Human And Computational Decision Making 15th International Conference on Human-Computer Interaction https://www.osti.gov/search/identifier:1145214 Document ID: 5319698

Richard Schiek, Eric R. Keiter, Christina E. Warrender, James Bradley Aimone, Heidi K. Thornquist, Thomas V. Russo, Jason Verley, Patricia J. Crossno, Corinne Teeter, Ting Mei, Sivasankaran Rajamanickam, (2013). Neuron Simulation and Analysis with Xyce Computational and Systems Neuroscience (Cosyne) 2013 https://www.osti.gov/search/identifier:1064135 Document ID: 5319132

Richard Schiek, Heidi K. Thornquist, Christina E. Warrender, Ting Mei, Corinne Michelle Teeter, James Bradley Aimone, (2012). NeuroXyce: Simulating neural systems with Xyce https://www.osti.gov/search/identifier:1096952 Document ID: 5313322

Corinne Michelle Teeter, Derek Trumbo, Christina E. Warrender, James Bradley Aimone, (2012). Neurons to Algorithms (N2A) neural modeling platform Society for Neuroscience Annual Meeting 2012 Document ID: 5314289

Derek Trumbo, Christina E. Warrender, James Bradley Aimone, Corinne Michelle Teeter, Fredrick Rothganger, (2012). Neurons to Algorithms neural circuit model development platform Neuroinformatics 2012 https://www.osti.gov/search/identifier:1061129 Document ID: 5312580