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Stanford CS224W: ML with Graphs | 2021 | Lecture 15.1 - Deep Generative Models for Graphs
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Jure Leskovec
Computer Science, PhD
To follow along with the course schedule and syllabus, visit:
#machinelearning #machinelearningcourse
Stanford CS224W: ML with Graphs | 2021 | Lecture 6.1 - Introduction to Graph Neural Networks
Stanford CS224W: ML with Graphs | 2021 | Lecture 13.1 - Community Detection in Networks
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.2 - Applications of Graph ML
Stanford CS224W: ML with Graphs | 2021 | Lecture 16.4 - Robustness of Graph Neural Networks
Stanford CS224W: ML with Graphs | 2021 | Lecture 9.1 - How Expressive are Graph Neural Networks
Stanford CS224W: ML with Graphs | 2021 | Lecture 2.3 - Traditional Feature-based Methods: Graph
Stanford CS224W: ML with Graphs | 2021 | Lecture 19.1 - Pre-Training Graph Neural Networks
Stanford CS224W: ML with Graphs | 2021 | Lecture 2.2 - Traditional Feature-based Methods: Link
Stanford CS224W: ML with Graphs | 2021 | Lecture 10.3 - Knowledge Graph Completion Algorithms
Stanford CS224W: ML with Graphs | 2021 | Lecture 2.1 - Traditional Feature-based Methods: Node
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.1 - Why Graphs
Stanford CS224W: ML with Graphs | 2021 | Lecture 16.1 - Limitations of Graph Neural Networks
Stanford CS224W: ML with Graphs | 2021 | Lecture 5.1 - Message passing and Node Classification
Stanford CS224W: ML with Graphs | 2021 | Lecture 5.2 - Relational and Iterative Classification
Stanford CS224W: ML with Graphs | 2021 | Lecture 12.1-Fast Neural Subgraph Matching & Counting
Stanford CS224W: ML with Graphs | 2021 | Lecture 16.2 - Position-Aware Graph Neural Networks
Stanford CS224W: ML with Graphs | 2021 | Lecture 15.2 - Graph RNN: Generating Realistic Graphs
Stanford CS224W: ML with Graphs | 2021 | Lecture 15.1 - Deep Generative Models for Graphs
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.2 - GraphSAGE Neighbor Sampling
Stanford CS224W: ML with Graphs | 2021 | Lecture 10.1-Heterogeneous & Knowledge Graph Embedding
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.2 - Basics of Deep Learning
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.3 - Choice of Graph Representation...
Stanford CS224W: ML with Graphs | 2021 | Lecture 9.2 - Designing the Most Powerful GNNs
Stanford CS224W: ML with Graphs | 2021 | Lecture 3.2-Random Walk Approaches for Node Embeddings
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