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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)

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TF-GNN: Graph Neural Networks in TensorFlow., , , , , , , , , and 14 other author(s). CoRR, (2022)Graph network simulators can learn discontinuous, rigid contact dynamics., , , , , , and . CoRL, volume 205 of Proceedings of Machine Learning Research, page 1157-1167. PMLR, (2022)Discovering objects and their relations from entangled scene representations., , , , , and . ICLR (Workshop), OpenReview.net, (2017)Graph neural networks in particle physics., , and . Mach. Learn. Sci. Technol., 2 (2): 21001 (2021)Inferring mass in complex physical scenes via probabilistic simulation., , , and . CogSci, cognitivesciencesociety.org, (2013)CompILE: Compositional Imitation Learning and Execution., , , , , , , and . ICML, volume 97 of Proceedings of Machine Learning Research, page 3418-3428. PMLR, (2019)Rediscovering orbital mechanics with machine learning., , , , and . Mach. Learn. Sci. Technol., 4 (4): 45002 (December 2023)Learning rigid dynamics with face interaction graph networks., , , , , , and . ICLR, OpenReview.net, (2023)Relational inductive biases, deep learning, and graph networks, , , , , , , , , and 1 other author(s). arXiv preprint arXiv:1806.01261, (2018)Visual Interaction Networks: Learning a Physics Simulator from Video., , , , , and . NIPS, page 4539-4547. (2017)