Graph Representation Learning (Stanford university) Published 2019-10-03 Download video MP4 360p Recommendations 51:06 Intro to graph neural networks (ML Tech Talks) 40:08 The Most Important Algorithm in Machine Learning 1:29:00 Graph Node Embedding Algorithms (Stanford - Fall 2019) 10:45 The Man Who Solved the $1 Million Math Problem...Then Disappeared 12:59 The Boundary of Computation 13:12 Water powered timers hidden in public restrooms 18:39 This equation will change how you see the world (the logistic map) 1:26:56 Page Ranking: Web as a Graph (Stanford University 2019) 59:32 Graph Representation Learning: William L. Hamilton - 2021 McGill AI Learnathon 20:18 Why Does Diffusion Work Better than Auto-Regression? 14:28 Graph Neural Networks - a perspective from the ground up 38:27 ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein 25:28 Watching Neural Networks Learn 31:39 Graph Embeddings 37:41 The math of how atomic nuclei stay together is surprisingly beautiful | Full movie #SoME2 1:12:20 Theoretical Foundations of Graph Neural Networks 34:48 The Unreasonable Effectiveness of JPEG: A Signal Processing Approach 18:16 Who cares about topology? (Inscribed rectangle problem) 1:22:31 Deep Graph Generative Models (Stanford University - 2019) Similar videos 20:27 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.3 - Choice of Graph Representation​ 16:50 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 17.2 - GraphSAGE Neighbor Sampling 14:44 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 3.1 - Node Embeddings 18:04 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 3.3 - Embedding Entire Graphs 11:55 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.1 - Why Graphs 35:41 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.3 - Deep Learning for Graphs 15:44 Stanford CS224W: ML with Graphs | 2021 | Lecture 15.1 - Deep Generative Models for Graphs 34:57 Stanford CS224W: ML with Graphs | 2021 | Lecture 10.1-Heterogeneous & Knowledge Graph Embedding 27:50 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.1 - Graph Augmentation for GNNs 20:27 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 1.2 - Applications of Graph ML 1:18:47 Stanford CS224W: Machine Learning w/ Graphs I 2023 I GNNs for Recommender Systems 49:48 Jure Leskovec: "Large-scale Graph Representation Learning" More results