Machine learning and spatial decomposition for large CT scans
Abstract not provided.
Publications
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Jump to search filtersThe ASC Advanced Machine Learning Initiative at Sandia National Laboratories: FY21 Accomplishments and FY22 Plans
Abstract not provided.
Model Parallelism with Spatial Decomposition of Volumetric Data for Deep Learning
Abstract not provided.
Neural Network Interatomic Potentials
In this project, we investigate the use of neural networks for the prediction of molecular properties, namely the interatomic potential. We use the machine learning package Tensorflow to build a variety of neural networks and compare performance with a popular Fortran package - Atomic Energy Networks (aenet). There are two primary goals for this work: 1) use the wide availability of different optimization techniques in Tensorflow to outperform aenet and 2) use new descriptors that can outperform Behler descriptors.
Data Analytics are Powerful -- Handle with Care
Abstract not provided.
Musgrave Ritual: Machine Learning Privacy Attacks and Defenses
Abstract not provided.
Machine Learning Applications for Molecular Dynamics Simulations
Abstract not provided.
Static Source Code Analysis Using Neural Networks
Abstract not provided.
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