Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.3 - Deep Learning for Graphs Published 2021-04-29 Download video MP4 360p Download video MP4 720p Recommendations 05:51 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.1 - A general Perspective on GNNs 07:50 Machine Learning vs Deep Learning 40:09 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.2 - A Single Layer of a GNN 23:08 Graphs, Vectors and Machine Learning - Computerphile 10:51 Simple Message Passing on Graphs 29:31 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 6.2 - Basics of Deep Learning 18:11 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.3 - Stacking layers of a GNN 05:49 AI vs Machine Learning 51:06 Intro to graph neural networks (ML Tech Talks) 14:28 Graph Neural Networks - a perspective from the ground up 37:12 KGC 2022 Keynote: 'Deep Learning with Knowledge Graphs' by Stanford's Prof. Jure Leskovec 58:04 Attention is all you need (Transformer) - Model explanation (including math), Inference and Training 03:26 What is Transfer Learning? [Explained in 3 minutes] 1:49:28 General Relativity Lecture 1 59:00 An Introduction to Graph Neural Networks: Models and Applications 08:00 What is Back Propagation 12:16 Fraud Detection with Graph Neural Networks 57:57 Lecture 1 | Introduction to Convolutional Neural Networks for Visual Recognition 10:31 Stanford CS224W: ML with Graphs | 2021 | Lecture 6.1 - Introduction to Graph Neural Networks Similar videos 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 24:26 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 5.3 - Collective Classification 14:44 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 3.1 - Node Embeddings 34:31 Stanford CS224W: ML with Graphs | 2021 | Lecture 10.3 - Knowledge Graph Completion Algorithms 27:50 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.1 - Graph Augmentation for GNNs 20:28 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 14.1 - Generative Models for Graphs 40:19 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.2 - Training Graph Neural Networks 35:40 Stanford CS224W: ML with Graphs | 2021 | Lecture 12.1-Fast Neural Subgraph Matching & Counting 27:30 Stanford CS224W: ML with Graphs | 2021 | Lecture 2.1 - Traditional Feature-based Methods: Node 25:54 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 12.3 - Finding Frequent Subgraphs 20:07 Stanford CS224W: ML with Graphs | 2021 | Lecture 19.1 - Pre-Training Graph Neural Networks 17:49 Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 8.3 - Setting up GNN Prediction Tasks 12:48 Stanford CS224W: ML with Graphs | 2021 | Lecture 4.4 - Matrix Factorization and Node Embeddings 23:57 Stanford CS224W: ML with Graphs | 2021 | Lecture 13.4 - Detecting Overlapping Communities More results