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Graph Neural Networks as Gradient Flows

Dynamical systems minimizing an energy are ubiquitous in geometry and ph...

Visualizing and Understanding Self-Supervised Vision Learning

Self-Supervised vision learning has revolutionized deep learning, becomi...

Understanding and Extending Subgraph GNNs by Rethinking Their Symmetries

Subgraph GNNs are a recent class of expressive Graph Neural Networks (GN...

Reconstructing Training Data from Trained Neural Networks

Understanding to what extent neural networks memorize training data is a...

pyKT: A Python Library to Benchmark Deep Learning based Knowledge Tracing Models

Knowledge tracing (KT) is the task of using students' historical learnin...

Sheaf Neural Networks with Connection Laplacians

A Sheaf Neural Network (SNN) is a type of Graph Neural Network (GNN) tha...