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Data-Driven and Knowledge-Driven Deep Learning for Battery Safety Modeling
Towards Third Wave AI: Interpretable, Robust Trustworthy Machine Learning for Diverse Applications in Science and Engineering
Data-driven Surrogate Modeling and Sensitivity Analysis for Particle-In-Cell Simulations of Plasma-Material Interactions
Interpreting Neural Network Models through Graph Representation Learning
Estimating the Errors of Randomized Algorithms via the Bootstrap
Stable Algorithms for Computing Forward Sensitivities for Particle-in-Cell Methods
Mathematica Tutorial
High Order Structure Preserving Numerical Methods for Euler Equations with Gravitation
Fast Stencil Computations using Fast Fourier Transforms and Gaussian Approximations
A Predictor-Corrector Strategy for Adaptivity in Dynamical Low-Rank Approximations
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