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Learning Mesh-Based Simulation with Graph Networks.

, , , и . CoRR, (2020)

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Alvaro Sánchez Cabrera

Marta González Sánchez

Alberto González-Sanchez

David Sánchez Sánchez

Alvaro Rietmüller

 

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Relational inductive biases, deep learning, and graph networks, , , , , , , , , и 1 other автор(ы). arXiv preprint arXiv:1806.01261, (2018)Discovering Symbolic Models from Deep Learning with Inductive Biases, , , , , , и . Advances in Neural Information Processing Systems, 33, стр. 17429--17442. Curran Associates, Inc., (2020)Physical Design using Differentiable Learned Simulators., , , , , , и . CoRR, (2022)Constraint-based graph network simulator., , , и . CoRR, (2021)Pre-training via Denoising for Molecular Property Prediction., , , , , , , , и . CoRR, (2022)WeatherBench 2: A benchmark for the next generation of data-driven global weather models., , , , , , , , , и 8 other автор(ы). CoRR, (2023)Constraint-based graph network simulator., , , и . ICML, том 162 из Proceedings of Machine Learning Research, стр. 18844-18870. PMLR, (2022)Graph Networks as Learnable Physics Engines for Inference and Control., , , , , , и . ICML, том 80 из Proceedings of Machine Learning Research, стр. 4467-4476. PMLR, (2018)Simple GNN Regularisation for 3D Molecular Property Prediction and Beyond., , , , , , , и . ICLR, OpenReview.net, (2022)Inverse Design for Fluid-Structure Interactions using Graph Network Simulators., , , , , , и . NeurIPS, (2022)