conftrace_

physics-informed learning

66 papers

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Also known as

PIL

Co-occurring keywords

partial differential equation (222) neural network (6616) dynamical system (398) diffusion model (3751) graph neural network (3962) gaussian process (1200) generative model (2892) uncertainty quantification (1393) differential equation (56) spatiotemporal prediction (21)

Papers

Physics Informed Deep Kernel Learning AISTATS 2022
Physics-Informed Long-Sequence Forecasting From Multi-Resolution Spatiotemporal Data IJCAI 2022
Scale-invariant Learning by Physics Inversion NIPS 2022
Physics-aware Spatiotemporal Modules with Auxiliary Tasks for Meta-Learning IJCAI 2021
Using Physics Knowledge for Learning Rigid-body Forward Dynamics with Gaussian Process Force Priors CORL 2021
Physics-Integrated Variational Autoencoders for Robust and Interpretable Generative Modeling NIPS 2021
Physics-Aware Downsampling with Deep Learning for Scalable Flood Modeling NIPS 2021
Discovering Hidden Physics Behind Transport Dynamics CVPR 2021
MC-LSTM: Mass-Conserving LSTM ICML 2021
Benchmarking Energy-Conserving Neural Networks for Learning Dynamics from Data L4DC 2021
Learning-based State Reconstruction for a Scalar Hyperbolic PDE under noisy Lagrangian Sensing L4DC 2021
Physics-informed Spline Learning for Nonlinear Dynamics Discovery IJCAI 2021
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints NIPS 2020
Weak Form Generalized Hamiltonian Learning NIPS 2020
HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems CORL 2018
Deep Hidden Physics Models: Deep Learning of Nonlinear Partial Differential Equations JMLR 2018