iDEA-iSAIL-Lab-UIUC / pyg-sslLinks
Graph Self-Supervised Learning Toolkit
☆43Updated 7 months ago
Alternatives and similar repositories for pyg-ssl
Users that are interested in pyg-ssl are comparing it to the libraries listed below
Sorting:
- GraphAny: Fully-inductive Node Classification on Arbitrary Graphs☆149Updated 11 months ago
- Uncertainty Quantification over Graph with Conformalized Graph Neural Networks (NeurIPS 2023)☆87Updated 2 years ago
- ☆91Updated 2 years ago
- Code for our paper "Attending to Graph Transformers"☆91Updated 2 years ago
- NeurIPS 2022 paper, SubHypergraph Inductive Neural nEtwork☆19Updated 2 years ago
- GraphXAI: Resource to support the development and evaluation of GNN explainers☆203Updated last year
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆123Updated last year
- This repository holds code and other relevant files for the Learning on Graphs 2022 tutorial "Graph Rewiring: From Theory to Applications…☆54Updated 3 years ago
- Accompanied repositories for our paper Graph foundation model☆230Updated last year
- It is a comprehensive resource hub compiling all graph papers accepted at the International Conference on Learning Representations (ICLR)…☆101Updated last year
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆50Updated last year
- Long Range Graph Benchmark, NeurIPS 2022 Track on D&B☆163Updated 2 years ago
- List of papers on NeurIPS2023☆90Updated 2 years ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆90Updated last year
- Graph Positional and Structural Encoder☆54Updated last year
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆181Updated 2 years ago
- All graph/GNN papers accepted at the International Conference on Machine Learning (ICML) 2024.☆233Updated last year
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆34Updated 2 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆173Updated last year
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆83Updated 4 years ago
- Dir-GNN is a machine learning model that enables learning on directed graphs.☆82Updated 2 years ago
- code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486☆99Updated 2 years ago
- A collection of graph foundation models including papers, codes, and datasets.☆155Updated 6 months ago
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs".☆91Updated last year
- A curated list of papers on graph structure learning (GSL).☆52Updated last year
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆205Updated 11 months ago
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- A collection of papers studying/improving the expressiveness of graph neural networks (GNNs)☆124Updated 2 years ago
- Kolmogorov Arnold Networks (KANs) for Graph Neural Networks (GNNs) and Tasks on Graphs☆65Updated last year
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆103Updated last year