partial differential equation

MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods ICML 2023 Mitigating Propagation Failures in Physics-informed Neural Networks using Retain-Resample-Release (R3) Sampling ICML 2023 Modeling Dynamics over Meshes with Gauge Equivariant Nonlinear Message Passing NeurIPS 2023 MultiAdam: Parameter-wise Scale-invariant Optimizer for Multiscale Training of Physics-informed Neural Networks ICML 2023 Neural Inverse Operators for Solving PDE Inverse Problems ICML 2023 Neural Network Approximations of PDEs Beyond Linearity: A Representational Perspective ICML 2023 Neural Operator: Learning Maps Between Function Spaces With Applications to PDEs JMLR 2023 Neural Q-learning for solving PDEs JMLR 2023 NeuralStagger: Accelerating Physics-constrained Neural PDE Solver with Spatial-temporal Decomposition ICML 2023 Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities ICLR 2023 Nonparametric Boundary Geometry in Physics Informed Deep Learning NeurIPS 2023 NUNO: A General Framework for Learning Parametric PDEs with Non-Uniform Data ICML 2023 Operator Learning with Neural Fields: Tackling PDEs on General Geometries NeurIPS 2023 PDE-Refiner: Achieving Accurate Long Rollouts with Neural PDE Solvers NeurIPS 2023 PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification NeurIPS 2023 PIXEL: Physics-Informed Cell Representations for Fast and Accurate PDE Solvers AAAI 2023 Random Feature Neural Networks Learn Black-Scholes Type PDEs Without Curse of Dimensionality JMLR 2023 Random Grid Neural Processes for Parametric Partial Differential Equations ICML 2023 Randomized Sparse Neural Galerkin Schemes for Solving Evolution Equations with Deep Networks NeurIPS 2023 Reinforcement Learning for Adaptive Mesh Refinement AISTATS 2023 Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning NeurIPS 2023 Scalable Transformer for PDE Surrogate Modeling NeurIPS 2023 Self-Consistent Velocity Matching of Probability Flows NeurIPS 2023 Self-Supervised Learning with Lie Symmetries for Partial Differential Equations NeurIPS 2023 Semi-supervised learning of partial differential operators and dynamical flows UAI 2023