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Relational inductive biases, deep learning, and graph networks, , , , , , , , , and 1 other author(s). arXiv preprint arXiv:1806.01261, (2018)Discovering Symbolic Models from Deep Learning with Inductive Biases, , , , , , and . Advances in Neural Information Processing Systems, 33, page 17429--17442. Curran Associates, Inc., (2020)Constraint-based graph network simulator., , , and . CoRR, (2021)Pre-training via Denoising for Molecular Property Prediction., , , , , , , , and . CoRR, (2022)Physical Design using Differentiable Learned Simulators., , , , , , and . CoRR, (2022)WeatherBench 2: A benchmark for the next generation of data-driven global weather models., , , , , , , , , and 8 other author(s). CoRR, (2023)Constraint-based graph network simulator., , , and . ICML, volume 162 of Proceedings of Machine Learning Research, page 18844-18870. PMLR, (2022)Graph Networks as Learnable Physics Engines for Inference and Control., , , , , , and . ICML, volume 80 of Proceedings of Machine Learning Research, page 4467-4476. PMLR, (2018)Neural General Circulation Models., , , , , , , , , and 6 other author(s). CoRR, (2023)Inverse Design for Fluid-Structure Interactions using Graph Network Simulators., , , , , , and . NeurIPS, (2022)