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

, , , and . Workshop on Temporal Graph Learning (TGL), NeurIPS, page 1--7. (2023)

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Multi-Sensor Data and Knowledge Fusion - A Proposal for a Terminology Definition., and . CoRR, (2020)Graph type expressivity and transformations., , , and . CoRR, (2021)Weisfeiler-Lehman goes Dynamic: An Analysis of the Expressive Power of Graph Neural Networks for Attributed and Dynamic Graphs., , , , , , and . CoRR, (2022)Time-Aware Robustness of Temporal Graph Neural Networks for Link Prediction (Extended Abstract)., and . TIME, volume 278 of LIPIcs, page 19:1-19:3. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2023)Student Research Abstract: Using Local Activity Encoding for Dynamic Graph Pooling in Stuctural-Dynamic Graphs. ACM/SIGAPP Symposium on Applied Computing (SAC), page 604--609. ACM, (2022)On the Extension of the Weisfeiler-Lehman Hierarchy by WL Tests for Arbitrary Graphs, , , , , and . Workshp on Mining and Learning on Graphs (MLG), ECML PKDD, page 1--13. (2022)Graph Neural Networks Designed for Different Graph Types: A Survey., , , and . CoRR, (2022)FDGNN: Fully Dynamic Graph Neural Network., , , and . CoRR, (2022)A Note on the Modeling Power of Different Graph Types, , , and . arXiv e-prints, (2021)Time-aware Robustness of Temporal Graph Neural Networks for Link Prediction, and . International Symposium on Temporal Representation and Reasoning (TIME), page 19:1--19:3. (2023)