Theoretical Foundations of Graph Neural Networks

Theoretical Foundations of Graph Neural Networks
Share:

Download MP3


Similar Tracks

Geometric Deep Learning: GNNs Beyond Permutation Equivariance Petar Veličković
Intro to graph neural networks (ML Tech Talks) TensorFlow
11. Introduction to Machine Learning MIT OpenCourseWare
Graph Representation Learning for Algorithmic Reasoning Petar Veličković
An Introduction to Graph Neural Networks: Models and Applications Microsoft Research
EPFL AI Center - A Physical perspective on Graph Neural Networks - Prof Michael Bronstein EPFL School of Computer and Communication Sciences
MIT 6.S191 (2023): Recurrent Neural Networks, Transformers, and Attention Alexander Amini
Everything is Connected: Deep Learning on Graphs Petar Veličković
Da Xu (Walmart Labs): Inductive Representation Learning on Temporal Graphs | AISC LLMs Explained - Aggregate Intellect - AI.SCIENCE
MIT Introduction to Deep Learning | 6.S191 Alexander Amini
Petar Veličković Graph Neural Networks: Geometric, Structural and Algorithmic Perspectives Part 1 Ellis Unit
Neuralising a Computer Scientist: The Story So Far Petar Veličković
Stanford CS224W: ML with Graphs | 2021 | Lecture 9.2 - Designing the Most Powerful GNNs Stanford Online
Graph Neural Networks in Computational Biology: A Personal Perspective - Petar Veličković Imperial College Computational Biology Society
Stanford CS224W: Machine Learning with Graphs | 2021 | Lecture 7.2 - A Single Layer of a GNN Stanford Online
[IPAM2019] Thomas Kipf "Unsupervised Learning with Graph Neural Networks" Zihao Zhu
Graph Neural Networks - a perspective from the ground up Alex Foo
Deep learning on graphs: successes, challenges | Graph Neural Networks | Michael Bronstein SAIConference
Categorical Deep Learning Petar Veličković
Learning the Structure of Graph Neural Networks | Mathias Niepert | heidelberg.ai heidelberg.ai