Single-Pass Contrastive Learning Can Work for Both Homophilic and Heterophilic Graph
Haonan Wang, Jieyu Zhang, Qi Zhu, Wei Huang, Kenji Kawaguchi, Xiaokui Xiao
Action editor: Sinead Williamson.
Universal Graph Continual Learning
#forgetting #continual #Graphs
Subgraph Permutation Equivariant Networks
Joshua Mitton, Roderick Murray-Smith
Action editor: Guillaume Rabusseau.
You Only Transfer What You Share: Intersection-Induced Graph Transfer Learning for Link Prediction
Wenqing Zheng, Edward W Huang, Nikhil Rao, Zhangyang Wang, Karthik Subbian
Action editor: Bo Han.
SMGRL: Scalable Multi-resolution Graph Representation Learning
'Clustering and Structural Robustness in Causal Diagrams', by Santtu Tikka, Jouni Helske, Juha Karvanen.
http://jmlr.org/papers/v24/21-1322.html
#causal #graphs #clusters
Rewiring with Positional Encodings for Graph Neural Networks
Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring
Shanchao Yang, MA KAILI, Baoxiang Wang, Tianshu Yu, Hongyuan Zha
Action editor: Nadav Cohen.
Understanding convolution on graphs via energies
Francesco Di Giovanni, James Rowbottom, Benjamin Paul Chamberlain et al.
Action editor: Guillaume Rabusseau.
#convolutions #convolutional #Graphs
Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities
Antonio Longa, Veronica Lachi, Gabriele Santin et al.
Action editor: Shinichi Nakajima.
Meta Continual Learning on Graphs with Experience Replay
Towards Better Generalization with Flexible Representation of Multi-Module Graph Neural Networks
HyunGeun Lee, Kijung Yoon
Action editor: Artem Babenko.
#Graphs #graph #generalization
I haven’t shared an outline yet, but this is like draft number 29 of the TOC for Exploring Graph Theory with Julia:
Part 1: “Pure” graph theory
1. What is a graph?
2. Telling graphs apart
3. Drawing graphs
Part 2: “Applied” graph theory
4. Graphs and maps
5. Graphs and industry
6. Graphs and games
7. Graphs and music
8. Graphs and the universe
9. Graphs and knowledge
Part 1 is almost mapped out and ready to be drafted!
#Graphs #graphTheory #julialang #math
If you (like me) like ASCII charts, I can highly recommend MRRArt (https://mrrartpro.com/) by @d4m1n
Number of cat snack servings per day
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DSpar: An Embarrassingly Simple Strategy for Efficient GNN training and inference via Degree-base...
Zirui Liu, Kaixiong Zhou, Zhimeng Jiang, Li Li, Rui Chen, Soo-Hyun Choi, Xia Hu
Action editor: Yujia Li.
A Simple Unified Method for Node Classification on Homophilous and Heterophilous Graphs
Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities
Self-Supervised Graph Representation Learning for Neuronal Morphologies
Marissa A. Weis, Laura Pede, Timo Lüddecke, Alexander S Ecker
Action editor: Robert Legenstein.
#neurons #Graphs #representations
Learning to Boost Resilience of Complex Networks via Neural Edge Rewiring