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CS224W: Machine Learning with Graphs Jure Leskovec, http ...

CS224W: Machine Learning with GraphsJure Leskovec, Stanford The class meets Tue and Thu 1:30-3:00pm Pacific Time in person Videos of the lectures will be recorded and posted on Canvas Structure of lectures: 60-70 minutes of a lecture During this time you can ask questions 10-20 minutes of a live Q&A/discussion session at the end of the lecture9/22/2021 Jure Leskovec, Stanford CS224W: Machine Learning with Graphs29/22/2021 Jure Leskovec, Stanford CS224W: Machine Learning with Graphs39/22/2021 Jure Leskovec, Stanford CS224W: Machine Learning with Graphs4 DateTopicDateTopicTue, Sep 211. Introduction; Machine Learning for GraphsTue, Oct 2611. Reasoning over Knowledge GraphsThu, Sep 232. Traditional Methods for ML on GraphsThu, Oct 2812. Frequent Subgraph Mining with GNNsTue, Sep 283.

Methods for node embeddings: DeepWalk, Node2Vec Graph Neural Networks: GCN, GraphSAGE, GAT, Theory of GNNs Knowledge graphs and reasoning: TransE, BetaE Deep generative models for graphs: GraphRNN Applications to Biomedicine, Science, Industry

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