Geometric Deep Learning: GNNs Beyond Permutation Equivariance Published 2021-12-08 Download video MP4 360p Recommendations 58:12 MIT Introduction to Deep Learning | 6.S191 14:28 Graph Neural Networks - a perspective from the ground up 18:51 Equivariant Neural Networks | Part 1/3 - Introduction 38:27 ICLR 2021 Keynote - "Geometric Deep Learning: The Erlangen Programme of ML" - M Bronstein 1:12:20 Theoretical Foundations of Graph Neural Networks 26:54 How Your Brain Organizes Information 1:30:19 AI for Drug Design - Lecture 16 - Deep Learning in the Life Sciences (Spring 2021) 43:26 Deep learning on graphs: successes, challenges | Graph Neural Networks | Michael Bronstein 1:02:50 MIT 6.S191: Recurrent Neural Networks, Transformers, and Attention 55:15 MIT 6.S191: Convolutional Neural Networks 51:06 Intro to graph neural networks (ML Tech Talks) 59:00 An Introduction to Graph Neural Networks: Models and Applications 1:08:06 Deep Learning Basics: Introduction and Overview 42:47 Why Everything You Thought You Knew About Quantum Physics is Different - with Philip Ball 29:15 Graph Neural Networks: A gentle introduction 16:48 How to use edge features in Graph Neural Networks (and PyTorch Geometric) 54:19 Backpropagation in Deep Learning | Part 1 | The What? 09:25 Graph Convolutional Networks (GCNs) made simple 1:15:20 Stanford CS229: Machine Learning Course, Lecture 1 - Andrew Ng (Autumn 2018) Similar videos 16:19 Equivariant Neural Networks | Part 3/3 - Transformers and GNNs 09:27 GNN Short Course Chapter 7 - Permutation Equivariance 59:12 AMMI Course "Geometric Deep Learning" - Lecture 1 (Introduction) - Michael Bronstein 09:27 How powerful are Graph Neural Networks? - Oxford Geometric Deep Learning 54:01 Geometric Deep Learning, Petar Veličković 1:01:52 AMMI 2022 Course "Geometric Deep Learning" - Seminar 3 (Equivariance in ML) - Geordie Williamson 2:06:03 Geometric Deep Learning (Part 1) 1:03:53 AMMI Course "Geometric Deep Learning" - Lecture 5 (Graphs & Sets I) - Petar Veličković 1:22:55 MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields 54:59 A New Perspective on Building Efficient and Expressive 3D Equivariant Graph Neural Networks 1:01:37 AMMI 2022 Course "Geometric Deep Learning" - Lecture 5 (Graphs & Sets) - Petar Veličković 47:25 Lecture 04: Point set-based modalities. Invariance and equivariance in learning 1:14:59 AMMI 2022 Course "Geometric Deep Learning" - Lecture 1 (Introduction) - Michael Bronstein More results