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Stanford CS224W Graph ML Tutorials
A collection of Graph Machine Learning tutorial blog posts created by Stanford students as the capstone project of CS224W.
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By Jure Leskovec, Federico Reyes Gomez, Weihua Hu
Federico Reyes Gómez
Feb 28, 2022
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WikiNet — An Experiment in Recurrent Graph Neural Networks
WikiNet — An Experiment in Recurrent Graph Neural Networks
By Alexander Hurtado + Aditya Iswara as part of the Stanford CS224W course project (Fall 2021)
Alexander Hurtado
Jan 13, 2022
Why should I trust my Graph Neural Network?
Why should I trust my Graph Neural Network?
An introduction to explainability methods for GNNs
CS224W GNN Explanations
Jan 15, 2022
Self-Supervised Learning For Graphs
Self-Supervised Learning For Graphs
By Paridhi Maheshwari, Jian Vora, Sharmila Reddy Nangi as part of the Stanford CS 224W course project.
Paridhi Maheshwari
Jan 18, 2022
Deep Learning on 3D Meshes
Deep Learning on 3D Meshes
A learned solution to node-level classification on irregular graphs via graph neural networks.
Anya Fries
Jan 25, 2022
Predicting Los Angeles Traffic with Graph Neural Networks
Predicting Los Angeles Traffic with Graph Neural Networks
By Julie Wang, Amelia Woodward, Tracy Cai as part of the Stanford CS224W course project.
Amelia Woodward
Jan 15, 2022
Alexa, Queue That Banger!
Alexa, Queue That Banger!
Recommending Spotify Playlist Tracks with Neural Collaborative Filtering Using Graph Machine Learning
Michał Skręta
Jan 15, 2022
How to Analyze Interacting Systems Using Graph Neural Networks
How to Analyze Interacting Systems Using Graph Neural Networks
Interactions are everywhere, from social dynamics to physical systems. Learn how to predict interactions using graph neural networks
Aljubrmj
Jan 15, 2022
Buy This!: Session-based Recommendation Using SR-GNN
Buy This!: Session-based Recommendation Using SR-GNN
Learn how to write a graph neural network for session-based recommendations
Eunjee Lynn Sung
Dec 29, 2021
C&S: Use the graph structure in your data with prediction post-processing
C&S: Use the graph structure in your data with prediction post-processing
Graph learning techniques are hard to add to existing ML pipelines. Using Correct&Smooth to refine your existing predictions by “smoothing”…
Andrew Kondrich
Jan 15, 2022
Recommender Systems with GNNs in PyG
Recommender Systems with GNNs in PyG
By Derrick Li, Peter Maldonado, Akram Sbaih as part of the Stanford CS224W (Machine course project.
Derrick Li
Jan 10, 2022
Graphs are All You Need: Generating Multimodal Representations for VQA
Graphs are All You Need: Generating Multimodal Representations for VQA
Visual Question Answering requires understanding and relating text and image inputs. Here we use Graph Neural Networks to reason over both…
Rajas Bansal
Jan 11, 2022
Using GNNs and Protein Expression Networks to Predict Alzheimer’s Disease Diagnosis
Using GNNs and Protein Expression Networks to Predict Alzheimer’s Disease Diagnosis
By Siddharth Doshi and Olamide Abiose as part of the Stanford CS224W course project.
Olamide Abiose
Jan 13, 2022
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