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Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing

V. Zaverkin, F. Alesiani, T. Maruyama, F. Errica, H. Christiansen, M. Takamoto, N. Weber, and M. Niepert. In Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), (2024)
DOI: https://doi.org/10.48550/arXiv.2405.14253

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Federico Pinchetti University of Stuttgart

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A Fair Comparison of Graph Neural Networks for Graph Classification.F. Errica, M. Podda, D. Bacciu, and A. Micheli. CoRR, (2019)Uncertainty-biased molecular dynamics for learning uniformly accurate interatomic potentialsV. Zaverkin, D. Holzmüller, H. Christiansen, F. Errica, F. Alesiani, M. Takamoto, M. Niepert, and J. Kästner. npj computational materials, 10 (1): 83 (2024)FA3L at SemEval-2017 Task 3: A ThRee Embeddings Recurrent Neural Network for Question Answering.G. Attardi, A. Carta, F. Errica, A. Madotto, and L. Pannitto. SemEval@ACL, page 299-304. Association for Computational Linguistics, (2017)Catastrophic Forgetting in Deep Graph Networks: A Graph Classification Benchmark.A. Carta, A. Cossu, F. Errica, and D. Bacciu. Frontiers Artif. Intell., (2022)Higher-Rank Irreducible Cartesian Tensors for Equivariant Message PassingV. Zaverkin, F. Alesiani, T. Maruyama, F. Errica, H. Christiansen, M. Takamoto, N. Weber, and M. Niepert. In Proceedings of the 38th Annual Conference on Neural Information Processing Systems (NeurIPS 2024), (2024)A Gentle Introduction to Deep Learning for Graphs.D. Bacciu, F. Errica, A. Micheli, and M. Podda. CoRR, (2019)Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing.D. Bacciu, F. Errica, and A. Micheli. ICML, volume 80 of Proceedings of Machine Learning Research, page 304-313. PMLR, (2018)

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Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing

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Federico Pinchetti University of Stuttgart

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copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing

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Federico Pinchetti University of Stuttgart

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Higher-Rank Irreducible Cartesian Tensors for Equivariant Message Passing