physics-informed neural network

Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling ICML 2023 MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks ICML 2023 NTFields: Neural Time Fields for Physics-Informed Robot Motion Planning ICLR 2023 Physics-Informed Model-Based Reinforcement Learning L4DC 2023 PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers AAAI 2023 Progressive Learning for Physics-informed Neural Motion Planning RSS 2023 Random Grid Neural Processes for Parametric Partial Differential Equations ICML 2023 Residual-based error bound for physics-informed neural networks UAI 2023 Separable Physics-Informed Neural Networks NeurIPS 2023 Universal Physics-Informed Neural Networks: Symbolic Differential Operator Discovery with Sparse Data ICML 2023 Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations NeurIPS 2022 Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers L4DC 2022 A Universal PINNs Method for Solving Partial Differential Equations with a Point Source IJCAI 2022 Auto-Physics-Encoder: Using Physics-Informed Latent Layer Two-Way Physics Flow for Monitoring Systems with Unobservability ACML 2022 Composing Partial Differential Equations with Physics-Aware Neural Networks ICML 2022 Generic bounds on the approximation error for physics-informed (and) operator learning NeurIPS 2022 Is L^2 Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? NeurIPS 2022 KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-zero Training Loss AAAI 2022 Learning Optimal K-Space Acquisition and Reconstruction Using Physics-Informed Neural Networks CVPR 2022 Machine Learning For Elliptic PDEs: Fast Rate Generalization Bound, Neural Scaling Law and Minimax Optimality ICLR 2022 Meta-Auto-Decoder for Solving Parametric Partial Differential Equations NeurIPS 2022 ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias ICML 2022 Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling L4DC 2022 NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation NeurIPS 2022 PDEBench: An Extensive Benchmark for Scientific Machine Learning NeurIPS 2022