Thermodynamically consistent physics-informed neural networks for hyperbolic systems
Abstract not provided.
Publications
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Jump to search filtersDevelopment of Machine Learned SNAP Potentials for Studying Radiation Damage in Materials
Abstract not provided.
Model Parallelism with Spatial Decomposition of Volumetric Data for Deep Learning
Abstract not provided.
Recent Advances in Adaptive Refinement of (Regression-Based) Multifidelity Surrogates for UQ
Abstract not provided.
Operational Quantum Tomography
Abstract not provided.
Coupling 1D Telegrapher Equations to 3D Maxwell's Equations with Applications to Pulsed Power
Abstract not provided.
Polynomial Chaos Expansions for Discrete Random Variables in Cyber Security Emulytics Experiments
Abstract not provided.
Solving stochastic inverse problems for property-structure linkage using data-consistent inversion and ML
Abstract not provided.
Evolving Spiking Circuit Motifs Using Weight Agnostic Neural Networks
Abstract not provided.
Use of Model Discrepancy and Model Selection as a Means of Informing Missing Physics
Abstract not provided.
Hybrid multi-level Monte Carlo polynomial chaos method for global sensitivity analysis
Abstract not provided.
Exploring important directions for multifidelity uncertainty quantification by basis adaptation method
Abstract not provided.
An Adaptive Basis Perspective to Improve Initialization and Accelerate Training of DNNs
Abstract not provided.
Design and Implementation of ETD Methods for Nonhydrostatic Atmosphere Models
Abstract not provided.
A Winding Road to Exascale Visualization
Abstract not provided.
Application of Multifidelity Uncertainty Quantification Methods to a Subsurface Transport Model
Abstract not provided.
Generalized Canonical Polyadic Tensor Decompositions for Streaming Data
Abstract not provided.
Multifidelity Monte Carlo Estimators for Robust Formulations in Optimization under Uncertainty
Abstract not provided.
Combined Eulerian and Lagrangian approaches in peridynamic material modeling
Abstract not provided.
Non-Gaussian noise characterization with factorial hidden Markov models
nPINNS: Nonlocal Physics-Informed Neural Networks
Abstract not provided.
Robustness and Validation of Model and Digital Twins Deployment
For digital twins (DTs) to become a central fixture in mission critical systems, a better understanding is required of potential modes of failure, quantification of uncertainty, and the ability to explain a model’s behavior. These aspects are particularly important as the performance of a digital twin will evolve during model development and deployment for real-world operations.
Building a VR motion simulator
Abstract not provided.
Peridynamic Model for Graphene Derived from Molecular Dynamics
Abstract not provided.
Implementing Calving Laws in Ice-Sheet Models using Level Set Methods
Abstract not provided.
Results 876–900 of 9,998