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Inductive Representation Learning on Large Graphs

, , and . (2017)cite arxiv:1706.02216Comment: Published in NIPS 2017; version with full appendix and minor corrections.

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Modelling Sparse Dynamical Systems with Compressed Predictive State Representations., , and . ICML (1), volume 28 of JMLR Workshop and Conference Proceedings, page 178-186. JMLR.org, (2013)Understanding the Performance of Knowledge Graph Embeddings in Drug Discovery., , , , , and . CoRR, (2021)Representation learning methods for computational social science.. Stanford University, USA, (2018)Generalizable Adversarial Attacks Using Generative Models., , and . CoRR, (2019)Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change, , and . arXiv:1605.09096 cs, (October 2018)arXiv: 1605.09096.Do Syntax Trees Help Pre-trained Transformers Extract Information?, , , and . EACL, page 2647-2661. Association for Computational Linguistics, (2021)NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphs., , , and . ICLR, OpenReview.net, (2022)Latent Variable Modelling with Hyperbolic Normalizing Flows., , , , and . ICML, volume 119 of Proceedings of Machine Learning Research, page 1045-1055. PMLR, (2020)Adversarial Example Games., , , , , , and . NeurIPS, (2020)Inducing Domain-Specific Sentiment Lexicons from Unlabeled Corpora., , , and . EMNLP, page 595-605. The Association for Computational Linguistics, (2016)