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

Learning Dynamical Coupled Operator For High-dimensional Black-box Partial Differential Equations IJCAI 2025
MMET: A Multi-Input and Multi-Scale Transformer for Efficient PDEs Solving IJCAI 2025
How Do Large Language Models Perform on PDE Discovery: A Coarse-to-fine Perspective EMNLP 2025
Physics-Informed Deep Learning and Compressive Collocation for High-Dimensional Diffusion-Reaction Equations: Practical Existence Theory and Numerics JMLR 2025
Physics-informed Kernel Learning JMLR 2025
Structure-Preserving Physics-Informed Neural Networks with Energy or Lyapunov Structure IJCAI 2024
AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields NIPS 2024
PirateNets: Physics-informed Deep Learning with Residual Adaptive Networks JMLR 2024
Fourier Neural Operators for Arbitrary Resolution Climate Data Downscaling JMLR 2024
A PDE-based Explanation of Extreme Numerical Sensitivities and Edge of Stability in Training Neural Networks JMLR 2024
Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization NIPS 2024
Operator learning without the adjoint JMLR 2024
Alias-Free Mamba Neural Operator NIPS 2024
PDE+: Enhancing Generalization via PDE with Adaptive Distributional Diffusion AAAI 2024
Boundary constrained Gaussian processes for robust physics-informed machine learning of linear partial differential equations JMLR 2024
Deep Backward and Galerkin Methods for the Finite State Master Equation JMLR 2024
RandNet-Parareal: a time-parallel PDE solver using Random Neural Networks NIPS 2024
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs NIPS 2024
PACE: Pacing Operator Learning to Accurate Optical Field Simulation for Complicated Photonic Devices NIPS 2024
Physics-constrained learning of PDE systems with uncertainty quantified port-Hamiltonian models L4DC 2024
Controlgym: Large-scale control environments for benchmarking reinforcement learning algorithms L4DC 2024
Physics-informed Neural Networks with Unknown Measurement Noise L4DC 2024
Efficient Learning of PDEs via Taylor Expansion and Sparse Decomposition into Value and Fourier Domains AAAI 2024
How does PDE order affect the convergence of PINNs? NIPS 2024
PDENNEval: A Comprehensive Evaluation of Neural Network Methods for Solving PDEs IJCAI 2024