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Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 19.2 - Hyperbolic Graph Embeddings
Stanford CS224W: ML with Graphs | 2021 | Lecture 19.1 - Pre-Training Graph Neural Networks
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.3 - Deep Learning for Graphs
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 11.2 - Answering Predictive Queries
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.3 - Choice of Graph Representation​
Stanford CS224W: ML with Graphs | 2021 | Lecture 19.3 - Design Space of Graph Neural Networks
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 4.2 - PageRank: How to Solve?
Hyperbolic Force-directed Graph Embedding
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.1 - A general Perspective on GNNs
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 5.3 - Collective Classification
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.4 - Scaling up by Simplifying GNNs
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.3 - Stacking layers of a GNN
