pbielak / graph-barlow-twinsLinks
The official implementation of the Graph Barlow Twins method with the experimental pipeline
☆31Updated 2 years ago
Alternatives and similar repositories for graph-barlow-twins
Users that are interested in graph-barlow-twins are comparing it to the libraries listed below
Sorting:
- A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …☆30Updated 4 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Updated 3 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆84Updated 2 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 4 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆67Updated 3 years ago
- Wasserstein Weisfeiler-Lehman Graph Kernels☆86Updated last year
- Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)☆53Updated last week
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 4 years ago
- Code of "Analyzing the Expressive Power of Graph Neural Networks in a Spectral Perspective" paper published in ICLR2021☆46Updated 4 years ago
- Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"☆97Updated 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 4 years ago
- Neo-GNNs: Neighborhood Overlap-aware Graph Neural Networks for Link Prediction☆38Updated 3 years ago
- A graph reliability toolbox based on PyTorch and PyTorch Geometric (PyG).☆90Updated last year
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- Generating PGM Explanation for GNN predictions☆76Updated 2 years ago
- [ICML 2022] "ProGCL: Rethinking Hard Negative Mining in Graph Contrastive Learning"☆46Updated 3 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆70Updated 2 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆118Updated 5 years ago
- Hypergraph representation learning: Hypergraph Networks with Hyperedge Neurons.☆44Updated 5 years ago
- Variational Graph Convolutional Networks☆23Updated 5 years ago
- Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"☆61Updated 4 years ago
- Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch☆62Updated 5 years ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆36Updated 4 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆49Updated last year
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆95Updated last year
- A curated list of publications and code about data augmentaion for graphs.☆63Updated 3 years ago
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆107Updated 6 months ago
- Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"☆59Updated 4 years ago
- [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization☆77Updated 2 years ago