Information propagation dynamics in Deep Graph Networks

arXiv:2410.10464 · cs.LG, cs.SI · Submitted 2024-10-14 · Read on arXiv

cs.LG, cs.SI

Submitted: 2024-10-14

Updated: 2026-10-01

Code: https://github.com/gravins/DGNs-for-schizophrenia

Terminology

• Abstraction — 1× in this paper · explained in 1 episode
• Representation Learning — 1× in this paper · explained in 2 episodes

Sources

• On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems
• Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
• Residual Gated Graph ConvNets
• A Note on Over-Smoothing for Graph Neural Networks
• Topology Adaptive Graph Convolutional Networks
• Adaptive Message Passing: A General Framework to Mitigate Oversmoothing, Oversquashing, and Underreaching
• DynGEM: Deep Embedding Method for Dynamic Graphs
• Generating Sequences With Recurrent Neural Networks
• Fake News Detection on Social Media using Geometric Deep Learning
• Graph Neural Ordinary Differential Equations
• A Survey on Oversmoothing in Graph Neural Networks
• TCL: Transformer-based Dynamic Graph Modelling via Contrastive Learning
• An Empirical Evaluation of Temporal Graph Benchmark

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