RXPHD / Lazy_GNN
LazyGNN: Large-Scale Graph Neural Networks via Lazy Propagation ICML_2023
☆12Updated last year
Alternatives and similar repositories for Lazy_GNN:
Users that are interested in Lazy_GNN are comparing it to the libraries listed below
- ☆29Updated 3 years ago
- Implementation of the paper "A New Perspective on the Effects of Spectrum in Graph Neural Networks"☆17Updated 2 years ago
- Pytorch implementation of EvenNet.☆20Updated 2 years ago
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- Ongoing project: a library for graph foundation model☆13Updated last year
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆30Updated 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
- 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
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- "HomoGCL: Rethinking Homophily in Graph Contrastive Learning" in KDD'23☆13Updated last year
- DP-GNN design that ensures both model weights and inference procedure differentially private (NeurIPS 2023)☆12Updated last year
- ☆20Updated 2 years ago
- ☆25Updated 2 years ago
- A curated list of Heterophilous Graph Self-Supervised Learning papers.☆15Updated 2 years ago
- Tail-GNN: Tail-Node Graph Neural Networks☆33Updated 3 years ago
- ☆14Updated 3 years ago
- Papers about developing DL methods on disassortative graphs☆48Updated 2 years ago
- PyTorch implementation of "Convolutional Neural Networks on Graphs with Chebyshev Approximation, Revisited"☆38Updated last year
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- Energetic GraphNeural Networks (EGNN) implementation based on Dirichlet Energy Constrained Learning.☆25Updated 3 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆21Updated last year
- Open-source datasets for paper "Fairness in Graph Mining: A Survey".☆18Updated 2 years ago
- Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".☆26Updated 2 years ago
- ☆54Updated 7 months ago
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 4 years ago
- ☆21Updated 2 years ago
- Yuhong Luo and Pan Li. Neighborhood-aware scalable temporal network representation learning. In Learning on Graphs, 2022.☆27Updated last year
- A graph benchmark library for heterophilic and heterogeneous graphs☆13Updated 2 months ago
- Official repository of "On Positional and Structural Node Features for Graph Neural Networks on Non-attributed Graphs", CIKM 2022☆17Updated 2 years ago
- the code of MoG☆15Updated 8 months ago