qitianwu / NodeFormer
The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"
☆304Updated last year
Alternatives and similar repositories for NodeFormer:
Users that are interested in NodeFormer are comparing it to the libraries listed below
- Representing Long-Range Context for Graph Neural Networks with Global Attention☆130Updated 3 years ago
- Official Pytorch code for Structure-Aware Transformer.☆257Updated 2 years ago
- Accompanied repositories for our paper Graph foundation model☆201Updated 5 months ago
- A graph transformer framework☆77Updated 2 years ago
- ☆156Updated 3 years ago
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆254Updated 3 years ago
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆122Updated 2 years ago
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆123Updated last year
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆194Updated 4 months ago
- Bag of Tricks for Graph Neural Networks.☆293Updated 9 months ago
- ☆171Updated last year
- Subgraph Neural Networks (NeurIPS 2020)☆193Updated 4 years ago
- ☆134Updated last year
- A curated list of graph data augmentation papers.☆307Updated last year
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆160Updated last year
- A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.☆208Updated 11 months ago
- AAAI'21: Data Augmentation for Graph Neural Networks☆191Updated last year
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆196Updated 2 months ago
- ☆87Updated last year
- ☆127Updated last month
- GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks☆157Updated 6 months ago
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆254Updated 5 months ago
- [GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)☆327Updated last year
- [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang…☆591Updated 9 months ago
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆156Updated last year
- [ICLR 2023 notable top-5%] Rethinking the Expressive Power of GNNs via Graph Biconnectivity (official implementation)☆104Updated last year
- Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)☆101Updated 3 years ago
- A Library for Dynamic Graph Learning (NeurIPS 2023)☆238Updated last year
- GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22☆512Updated 2 years ago
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆88Updated 6 months ago