Alternatives and similar repositories for NAGphormer:

Users that are interested in NAGphormer are comparing it to the libraries listed below

• zaixizhang / ANS-GT
  NeurIPS'22 Spotlight paper "Hierarchical Graph Transformer with Adaptive Node Sampling"
  ☆49Updated last year
• yandex-research / heterophilous-graphs
  A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
  ☆107Updated last year
• ivam-he / BernNet
  PyTorch implementation of "BernNet: Learning Arbitrary Graph Spectral Filters via Bernstein Approximation"
  ☆53Updated last year
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆76Updated 3 months ago
• jianhao2016 / AllSet
  This is the GitHub repository for our ICLR22 paper: "You are AllSet: A Multiset Function Framework for Hypergraph Neural Networks"
  ☆94Updated last year
• ICT-GIMLab / SeHGNN
  ☆104Updated last year
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆79Updated 2 years ago
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆66Updated 8 months ago
• LUMIA-Group / OrderedGNN
  The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).
  ☆41Updated 11 months ago
• YangLing0818 / VQGraph
  [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
  ☆89Updated 11 months ago
• qwerfdsaplking / Graph-Trans
  A graph transformer framework
  ☆77Updated 2 years ago
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆101Updated 2 years ago
• Shen-Lab / GraphCL_Automated
  [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…
  ☆110Updated 5 months ago
• CUAI / Non-Homophily-Large-Scale
  [NeurIPS 2021] Large Scale Learning on Non-Homophilous Graphs: New Benchmarks and Strong Simple Methods
  ☆120Updated 2 years ago
• AndyJZhao / GLEM
  ☆125Updated last year
• snap-research / graphless-neural-networks
  [ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)
  ☆88Updated 3 months ago
• liun-online / HeCo
  The source code of HeCo
  ☆159Updated 2 years ago
• zaixizhang / Graph_Transformer
  A pytorch implementation of graph transformer for node classification
  ☆30Updated last year
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆42Updated 2 years ago
• MingChen-Sun / GPPT
  ☆57Updated 2 years ago
• Ffffffffire / HINormer
  ☆33Updated last year
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆97Updated 11 months ago
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆26Updated last year
• Graph-COM / PEG
  ☆38Updated last year
• jianhao2016 / GPRGNN
  ☆131Updated last year
• bdy9527 / FAGCN
  ☆95Updated 3 years ago
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆88Updated 3 years ago
• CurryTang / TSGFM
  NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
  ☆39Updated last month
• nerdslab / bgrl
  PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
  ☆81Updated last year
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆87Updated 3 years ago