qitianwu / NodeFormerLinks
The official implementation of NeurIPS22 spotlight paper "NodeFormer: A Scalable Graph Structure Learning Transformer for Node Classification"
☆313Updated last year
Alternatives and similar repositories for NodeFormer
Users that are interested in NodeFormer are comparing it to the libraries listed below
Sorting:
- NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs☆132Updated last year
- Official Pytorch code for Structure-Aware Transformer.☆262Updated 2 years ago
- Official Implementation of ICML 2023 paper: "A Generalization of ViT/MLP-Mixer to Graphs"☆167Updated last year
- [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods☆124Updated 3 years ago
- A graph transformer framework☆78Updated 3 years ago
- A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).☆210Updated 11 months ago
- Representing Long-Range Context for Graph Neural Networks with Global Attention☆130Updated 3 years ago
- [ICLR'22][KDD'22][IJCAI'24][NeurIPS'25] Implementation of "Graph Condensation for Graph Neural Networks"☆141Updated last month
- A paper collection about automated graph learning☆97Updated last year
- A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?☆121Updated 2 years ago
- Bag of Tricks for Graph Neural Networks.☆299Updated last year
- [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)☆95Updated last year
- A comprehensive benchmark of Graph Structure Learning (NeurIPS 2023 Datasets and Benchmarks Track)☆121Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆66Updated last year
- GraphPrompt: Unifying Pre-Training and Downstream Tasks for Graph Neural Networks☆162Updated last year
- ☆131Updated 8 months ago
- A fundational graph learning framework that solves cross-domain/cross-task classification problems using one model.☆239Updated last year
- This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"☆104Updated 2 years ago
- GraphMAE2: A Decoding-Enhanced Masked Self-Supervised Graph Learner in WWW'23☆176Updated 2 years ago
- NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"☆52Updated 2 years ago
- ☆139Updated 2 years ago
- Accompanied repositories for our paper Graph foundation model☆228Updated last year
- A curated list of graph data augmentation papers.☆314Updated last year
- AAAI'21: Data Augmentation for Graph Neural Networks☆195Updated last year
- Transformer-based Spectral Graph Neural Networks☆85Updated last year
- ☆104Updated 2 years ago
- Parameterized Explainer for Graph Neural Network☆140Updated last year
- [GRL+ @ ICML 2020] PyTorch implementation for "Deep Graph Contrastive Representation Learning" (https://arxiv.org/abs/2006.04131v2)☆338Updated last year
- This repository contains the resources on graph neural network (GNN) considering heterophily.☆264Updated last year
- Source code for GNN-LSPE (Graph Neural Networks with Learnable Structural and Positional Representations), ICLR 2022☆265Updated 3 years ago