physics-informed learning

Physics-constrained learning of PDE systems with uncertainty quantified port-Hamiltonian models L4DC 2024 Physics-Informed Graph Neural Networks for Water Distribution Systems AAAI 2024 Physics-Informed Trajectory Prediction for Autonomous Driving under Missing Observation IJCAI 2024 PlantPlotGAN: A Physics-Informed Generative Adversarial Network for Plant Disease Prediction WACV 2024 Sliced Denoising: A Physics-Informed Molecular Pre-Training Method ICLR 2024 SNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural Networks AAAI 2024 Social Physics Informed Diffusion Model for Crowd Simulation AAAI 2024 Transfer Learning Using Inaccurate Physics Rule for Streamflow Prediction IJCAI 2024 Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification MIDL 2023 Compositional Learning of Dynamical System Models Using Port-Hamiltonian Neural Networks L4DC 2023 Gaussian Process Priors for Systems of Linear Partial Differential Equations with Constant Coefficients ICML 2023 Guiding continuous operator learning through Physics-based boundary constraints ICLR 2023 INO: Invariant Neural Operators for Learning Complex Physical Systems with Momentum Conservation AISTATS 2023 InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion ICCV 2023 Neumann Network With Recursive Kernels for Single Image Defocus Deblurring CVPR 2023 Nonparametric Boundary Geometry in Physics Informed Deep Learning NeurIPS 2023 Physics-Driven Turbulence Image Restoration with Stochastic Refinement ICCV 2023 Physics-Informed Bayesian Optimization of Variational Quantum Circuits NeurIPS 2023 PICProp: Physics-Informed Confidence Propagation for Uncertainty Quantification NeurIPS 2023 ResoNet: Noise-Trained Physics-Informed MRI Off-Resonance Correction NeurIPS 2023 SyncTREE: Fast Timing Analysis for Integrated Circuit Design through a Physics-informed Tree-based Graph Neural Network NeurIPS 2023 AutoIP: A United Framework to Integrate Physics into Gaussian Processes ICML 2022 Auto-Physics-Encoder: Using Physics-Informed Latent Layer Two-Way Physics Flow for Monitoring Systems with Unobservability ACML 2022 Deep Learning for Model Correction in Cardiac Electrophysiological Imaging MIDL 2022 Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning ICLR 2022