conftrace_

partial differential equation

222 papers

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Also known as

PDE

Co-occurring keywords

physics-informed neural network (97) neural network (6616) neural operator (74) operator learning (48) neural network optimization (1293) scientific machine learning (23) graph neural network (3962) inverse problem (240) physics-informed learning (66) fourier neural operator (22)

Papers

Meta Learning of Interface Conditions for Multi-Domain Physics-Informed Neural Networks ICML 2023
Learning Neural Constitutive Laws from Motion Observations for Generalizable PDE Dynamics ICML 2023
Learning Neural PDE Solvers with Parameter-Guided Channel Attention ICML 2023
Transfer Learning Enhanced DeepONet for Long-Time Prediction of Evolution Equations AAAI 2023
Exploration on Physics-Informed Neural Networks on Partial Differential Equations (Student Abstract) AAAI 2023
Scalable Transformer for PDE Surrogate Modeling NIPS 2023
Geometry-Informed Neural Operator for Large-Scale 3D PDEs NIPS 2023
Self-Consistent Velocity Matching of Probability Flows NIPS 2023
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning NIPS 2023
Separable Physics-Informed Neural Networks NIPS 2023
Learning Space-Time Continuous Latent Neural PDEs from Partially Observed States NIPS 2023
PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification NIPS 2023
Lie Point Symmetry and Physics-Informed Networks NIPS 2023
LagrangeBench: A Lagrangian Fluid Mechanics Benchmarking Suite NIPS 2023
Operator Learning with Neural Fields: Tackling PDEs on General Geometries NIPS 2023
Strategic Distribution Shift of Interacting Agents via Coupled Gradient Flows NIPS 2023
Deep Equilibrium Based Neural Operators for Steady-State PDEs NIPS 2023
CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra NIPS 2023
Random Feature Neural Networks Learn Black-Scholes Type PDEs Without Curse of Dimensionality JMLR 2023
Semi-supervised learning of partial differential operators and dynamical flows UAI 2023
Learning Physics-Informed Neural Networks without Stacked Back-propagation AISTATS 2023
Meta-Auto-Decoder for Solving Parametric Partial Differential Equations NIPS 2022
Learning Operators with Coupled Attention JMLR 2022
Learning to Solve PDE-constrained Inverse Problems with Graph Networks ICML 2022
M2N: Mesh Movement Networks for PDE Solvers NIPS 2022