nghiahhnguyen / Graph-Matching-Networks-PyTorchLinks
This is a **reimplementation** of the ICLR 2019 paper "Graph Matching Networks for Learning the Similarity of Graph Structured Objects" (Li et al.) in PyTorch.
☆23Updated 4 years ago
Alternatives and similar repositories for Graph-Matching-Networks-PyTorch
Users that are interested in Graph-Matching-Networks-PyTorch are comparing it to the libraries listed below
Sorting:
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆115Updated last year
- ☆56Updated 5 years ago
- H2MN: Graph Similarity Learning with Hierarchical Hypergraph Matching Networks (KDD-2021)☆57Updated 3 years ago
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆81Updated 3 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆71Updated 9 months ago
- Official Code Repository for the paper "Accurate Learning of Graph Representations with Graph Multiset Pooling" (ICLR 2021)☆107Updated 3 years ago
- Adversarial Graph Augmentation to Improve Graph Contrastive Learning☆90Updated 3 years ago
- Code for "Multilevel Graph Matching Networks for Deep Graph Similarity Learning"☆45Updated 4 years ago
- Representing Long-Range Context for Graph Neural Networks with Global Attention☆130Updated 3 years ago
- Code for ICDM2020 full paper: "Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning"☆46Updated 3 years ago
- Source code for From Stars to Subgraphs (ICLR 2022)☆71Updated last year
- Parameterized Explainer for Graph Neural Network☆139Updated last year
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆106Updated 5 months ago
- Implementation for Simple Spectral Graph Convolution in ICLR 2021☆85Updated 3 years ago
- Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).☆80Updated 4 years ago
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆81Updated 3 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆105Updated last year
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆171Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆125Updated 3 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆132Updated last year
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆64Updated 2 years ago
- Graph meta learning via local subgraphs (NeurIPS 2020)☆126Updated last year
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆84Updated 2 years ago
- Official implementation of our FLAG paper (CVPR2022)☆145Updated 3 years ago
- The official implementation of DropGNN: Random Dropouts Increase the Expressiveness of Graph Neural Networks (NeurIPS 2021)☆26Updated 3 years ago
- Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"☆89Updated 4 years ago
- ☆57Updated 4 years ago
- Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism"☆61Updated 4 years ago
- Rex Ying's Ph.D. Thesis, Stanford University☆41Updated 3 years ago
- Graph Representation Learning via Graphical Mutual Information Maximization☆117Updated 5 years ago