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Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems.

, , и . CoRR, (2021)

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Xun Wang

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Jian Wang

Jian Wang

Jian Wang

 

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Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems., , и . CoRR, (2021)PhyCRNet: Physics-informed Convolutional-Recurrent Network for Solving Spatiotemporal PDEs., , , , и . CoRR, (2021)SSR-VFD: Spatial Super-Resolution for Vector Field Data Analysis and Visualization., , , , , , , и . PacificVis, стр. 71-80. IEEE, (2020)Product Data Modeling for Design Collaboration., и . CSCWD, стр. 321-326. IEEE, (2007)Bayesian Spline Learning for Equation Discovery of Nonlinear Dynamics with Quantified Uncertainty., , , и . NeurIPS, (2022)Physics-informed Deep Super-resolution for Spatiotemporal Data., , , , , , и . CoRR, (2022)Probabilistic Physics-integrated Neural Differentiable Modeling for Isothermal Chemical Vapor Infiltration Process., , , , и . CoRR, (2023)SeismicNet: Physics-informed neural networks for seismic wave modeling in semi-infinite domain., , , , , и . Comput. Phys. Commun., (2024)Knowledge representation in an agent-based collaborative product design environment., и . CSCWD (1), стр. 423-428. IEEE Computer Society, (2005)Predicting Physics in Mesh-reduced Space with Temporal Attention., , , , и . ICLR, OpenReview.net, (2022)