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Marked Neural Spatio-Temporal Point Process Involving a Dynamic Graph Neural Network

, , , и . Workshop on Temporal Graph Learning (TGL), NeurIPS, стр. 1--7. (2023)

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Alice Gerlach

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Другие публикации лиц с тем же именем

Continuous-time generative graph neural network for attributed dynamic graphs: student research abstract.. SAC, стр. 600-603. ACM, (2022)Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs, , , , , , и . arXiv e-prints, (2022)Student Research Abstract: Continuous-Time Generative Graph Neural Network for Attributed Dynamic Graphs. ACM/SIGAPP Symposium on Applied Computing (SAC), стр. 600--603. ACM, (2022)FDGNN: Fully Dynamic Graph Neural Network, , , и . arXiv e-prints, (2022)Graph Neural Networks Designed for Different Graph Types: A Survey, , , и . arXiv e-prints, (2022)On the Extension of the Weisfeiler-Lehman Hierarchy by WL Tests for Arbitrary Graphs, , , , , и . Workshp on Mining and Learning on Graphs (MLG), ECML PKDD, стр. 1--13. (2022)A Note on the Modeling Power of Different Graph Types, , , и . arXiv e-prints, (2021)Weisfeiler–Lehman goes dynamic: An analysis of the expressive power of Graph Neural Networks for attributed and dynamic graphs, , , , , , и . Neural Networks, (2024)Graph Pooling Provably Improves Expressivity, , , и . Workshop on New Frontiers in Graph Learning, NeurIPS, стр. 1--7. (2023)Graph Neural Networks Designed for Different Graph Types: A Survey., , , и . Trans. Mach. Learn. Res., (2023)