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LabelFree-DNN-Surrogate
Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep LearninggraphGalerkin
Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problemsPhysics-constrained-Bayesian-deep-learning
Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy DataPIMBRL
Physics-informed Dyna-style model-based deep reinforcement learning for dynamic controlPICNNSR
Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels -- parametric forward SR and boundary inferencePPNN
Predicting parametric spatiotemporal dynamics by multi-resolution PDE structure-preserved deep learningPiNDiff-manufacturing
Physics-integrated neural differentiable model for composites manufacturingbaselineOperatorLearner
A group of baseline model for spatiotemporal operator learningLove Open Source and this site? Check out how you can help us