physics-informed neural network

Scaling physics-informed hard constraints with mixture-of-experts ICLR 2024 Solving High Frequency and Multi-Scale PDEs with Gaussian Processes ICLR 2024 Space-Time Continuous PDE Forecasting using Equivariant Neural Fields NeurIPS 2024 Stochastic Taylor Derivative Estimator: Efficient amortization for arbitrary differential operators NeurIPS 2024 Structure-Preserving Physics-Informed Neural Networks with Energy or Lyapunov Structure IJCAI 2024 The Challenges of the Nonlinear Regime for Physics-Informed Neural Networks NeurIPS 2024 Understanding the difficulty of solving Cauchy problems with PINNs L4DC 2024 Achieving High Accuracy with PINNs via Energy Natural Gradient Descent ICML 2023 A Continuous-time Stochastic Gradient Descent Method for Continuous Data JMLR 2023 A Generalizable Physics-informed Learning Framework for Risk Probability Estimation L4DC 2023 Bi-level Physics-Informed Neural Networks for PDE Constrained Optimization using Broyden's Hypergradients ICLR 2023 Competitive Physics Informed Networks ICLR 2023 CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions NeurIPS 2023 DMIS: Dynamic Mesh-Based Importance Sampling for Training Physics-Informed Neural Networks AAAI 2023 EINNs: Epidemiologically-Informed Neural Networks AAAI 2023 Exploration on Physics-Informed Neural Networks on Partial Differential Equations (Student Abstract) AAAI 2023 Gradient Descent Finds the Global Optima of Two-Layer Physics-Informed Neural Networks ICML 2023 Harmonic Neural Networks ICML 2023 How to Learn and Generalize From Three Minutes of Data: Physics-Constrained and Uncertainty-Aware Neural Stochastic Differential Equations CoRL 2023 Hypernetwork-based Meta-Learning for Low-Rank Physics-Informed Neural Networks NeurIPS 2023 Implicit Stochastic Gradient Descent for Training Physics-Informed Neural Networks AAAI 2023 Improved Training of Physics-Informed Neural Networks Using Energy-Based Priors: a Study on Electrical Impedance Tomography ICLR 2023 Learning Physics-Informed Neural Networks without Stacked Back-propagation AISTATS 2023 Lie Point Symmetry and Physics-Informed Networks NeurIPS 2023 Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks ICML 2023