conftrace_

physics-informed neural network

97 papers

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Also known as

PINNS PINN

Co-occurring keywords

partial differential equation (222) neural network optimization (1293) inductive bia (272) differential equation (56) dynamical system (398) neural ordinary differential equation (139) operator learning (48) ordinary differential equation (139) gradient descent (1144) automatic differentiation (77)

Papers

A Universal PINNs Method for Solving Partial Differential Equations with a Point Source IJCAI 2022
ModLaNets: Learning Generalisable Dynamics via Modularity and Physical Inductive Bias ICML 2022
KAM Theory Meets Statistical Learning Theory: Hamiltonian Neural Networks with Non-zero Training Loss AAAI 2022
Physics-Informed Implicit Representations of Equilibrium Network Flows NIPS 2022
Accelerated Training of Physics-Informed Neural Networks (PINNs) using Meshless Discretizations NIPS 2022
Is $L^2$ Physics Informed Loss Always Suitable for Training Physics Informed Neural Network? NIPS 2022
Generic bounds on the approximation error for physics-informed (and) operator learning NIPS 2022
Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling L4DC 2022
Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers L4DC 2022
Learning Optimal K-Space Acquisition and Reconstruction Using Physics-Informed Neural Networks CVPR 2022
NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation NIPS 2022
Spline-PINN: Approaching PDEs without Data Using Fast, Physics-Informed Hermite-Spline CNNs AAAI 2022
Composing Partial Differential Equations with Physics-Aware Neural Networks ICML 2022
PDEBench: An Extensive Benchmark for Scientific Machine Learning NIPS 2022
Meta-Auto-Decoder for Solving Parametric Partial Differential Equations NIPS 2022
Auto-Physics-Encoder: Using Physics-Informed Latent Layer Two-Way Physics Flow for Monitoring Systems with Unobservability ACML 2022
Learning Contact Dynamics using Physically Structured Neural Networks AISTATS 2021
Characterizing possible failure modes in physics-informed neural networks NIPS 2021
Automating Discovery of Physics-Informed Neural State Space Models via Learning and Evolution L4DC 2021
DPM: A Novel Training Method for Physics-Informed Neural Networks in Extrapolation AAAI 2021
Soft Multicopter Control Using Neural Dynamics Identification CORL 2020
Hamiltonian Neural Networks NIPS 2019