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Learning and Reasoning with Graph-Structured Representations (ICML 2019 Workshop) Learning and Reasoning with Graph-Structured Representations ICML 2019 Workshop Overview Schedule Accepted Papers All talk recordings are now available. You can find the links in the schedule . Overview Learning and reasoning with graph-structured representations is gaining increasing interest in both academia and industry, due to its fundamental advantages over more traditional unstructured methods in supporting interpretability, causality, and transferability / inductive generalization. Recently, there is a surge of new techniques in the context of deep learning, such as graph neural networks, for learning graph representations and performing reasoning and prediction, which have achieved impressive progress. However, it can still be a long way to go to obtain satisfactory results in long-range multi-step reasoning, scalable learning with very large gr...
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