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@graphml

Graph Machine Learning

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Publié20 mai20/05/2023 08:56
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Graph ML News (May 20th) The NeurIPS deadline has passed so we could finally disconnect from the cluster, breathe in some fresh air and get ready for the supplementary deadline and/or paper bidding depending on your status. The Workshop on Mining and Learning with Graph (MLG) at KDD’23 accepts submissions until May 30th. This year KDD will feature both MLG and Graph Learning Benchmarks (GLB), so two more reasons to visit Long Beach and chat with the fellow graph folks 😉 CS224W, one of the best graph courses from Stanford, started publishing project reports of the Winter 2023 cohort: some new articles include solving TSP with GNNs, approaching code similarity, and building music recommendation system with GNNs. More reports will be published within the next few weeks. Weekend reading: DRew: Dynamically Rewired Message Passing with Delay feat. Michael Bronstein and Francesco Di Giovanni (ICML’23) Random Edge Coding: One-Shot Bits-Back Coding of Large Labeled Graphs (ICML’23) Can Language Models Solve Graph Problems in Natural Language? On the Connection Between MPNN and Graph Transformer