qslim / gnn-spectrum
Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"
☆17Updated 2 years ago
Alternatives and similar repositories for gnn-spectrum:
Users that are interested in gnn-spectrum are comparing it to the libraries listed below
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- ☆29Updated 3 years ago
- ☆20Updated 2 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [ICML 2022] pGNN, p-Laplacian Based Graph Neural Networks☆27Updated 2 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- Pytorch implementation of EvenNet.☆19Updated 2 years ago
- Official repository for ICLR'23 paper: Multi-task Self-supervised Graph Neural Network Enable Stronger Task Generalization☆39Updated 2 years ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆31Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆56Updated last year
- This repo contains a reference implementation for the paper "Breaking the Limit of Graph Neural Networks by Improving the Assortativity o…☆32Updated 3 years ago
- "HomoGCL: Rethinking Homophily in Graph Contrastive Learning" in KDD'23☆12Updated last year
- Code for GBK-GNN (paper accepted by WWW2022)☆15Updated 2 years ago
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- [ICLR 2023] "Graph Domain Adaptation via Theory-Grounded Spectral Regularization" by Yuning You, Tianlong Chen, Zhangyang Wang, Yang Shen☆21Updated 2 years ago
- Codes for "Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks"☆37Updated last year
- Node Dependent Local Smoothing for Scalable Graph Learning (NeurIPS'21, Spotlight)☆21Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆41Updated 2 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 3 years ago
- WWW2021: Interpreting and Unifying Graph Neural Networks with An Optimization Framework☆14Updated 3 years ago
- Code and dataset for paper "GRAND+: Scalable Graph Random Neural Networks"☆33Updated 2 years ago
- A Note On Over-Smoothing for Graph Neural Network☆19Updated 4 years ago
- PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"☆35Updated last year
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆37Updated 4 years ago
- ☆13Updated 3 years ago
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆35Updated last year
- ☆10Updated 3 years ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago