THUDM / GraphMAE2
GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23
☆138Updated last year
Related projects ⓘ
Alternatives and complementary repositories for GraphMAE2
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆171Updated 9 months ago
- ☆54Updated 2 years ago
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated 5 months ago
- [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders☆77Updated last week
- GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks☆145Updated 2 weeks ago
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆72Updated last year
- [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"☆77Updated 2 years ago
- [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification☆90Updated 8 months ago
- ☆44Updated last year
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆109Updated 2 months ago
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆94Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆50Updated 10 months ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆118Updated 2 years ago
- The source code of HeCo☆158Updated 2 years ago
- Code for NeurIPS 2022 paper "Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discriminat…☆54Updated last year
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆159Updated 8 months ago
- [WWW'22] Towards Unsupervised Deep Graph Structure Learning☆129Updated last year
- A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.☆178Updated 5 months ago
- GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22☆470Updated last year
- ☆30Updated last year
- Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"☆74Updated 2 years ago
- Papers about out-of-distribution generalization on graphs.☆155Updated last year
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆112Updated 8 months ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆80Updated last year
- An official source code for paper "Graph Anomaly Detection via Multi-Scale Contrastive Learning Networks with Augmented View", accepted b…☆49Updated 11 months ago
- ☆116Updated last year
- Some GNNs are implemented using PyG for node classification tasks, including: GCN, GraphSAGE, SGC, GAT, R-GCN and HAN (Heterogeneous Grap…☆125Updated last year
- Accompanied repositories for our paper Graph foundation model☆144Updated 2 months ago
- A repository contains a collection of resources and papers on Imbalance Learning On Graphs☆84Updated 2 months ago