NineAbyss / ZeroG

Related projects: ⓘ

• cshhzhao / GCOPE
  Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…
  ☆21Updated 3 weeks ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆44Updated 8 months ago
• tengxiao1 / Awesome-Graph-Contrastive-Learning-with-Heterophily
  Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily
  ☆29Updated 10 months ago
• CurryTang / TSGFM
  ☆19Updated last week
• zyzisastudyreallyhardguy / GOAL-Graph-Complementary-Learning
  The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…
  ☆13Updated last year
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆41Updated 2 years ago
• NineAbyss / GLBench
  GLBench: A Comprehensive Benchmark for Graphs with Large Language Models
  ☆27Updated last week
• zjunet / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆24Updated 11 months ago
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆47Updated last year
• LuckyTiger123 / GPF
  The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.
  ☆17Updated 11 months ago
• liun-online / CoGSL
  Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression
  ☆23Updated 6 months ago
• ivam-he / PSHGCN
  ☆12Updated last year
• YuanchenBei / Awesome-Graph-Transfer-Learning
  A curated list of papers on graph transfer learning (GTL).
  ☆13Updated 10 months ago
• yandex-research / heterophilous-graphs
  A Critical Look at the Evaluation of GNNs under Heterophily: Are We Really Making Progress?
  ☆88Updated last year
• BUPT-GAMMA / Uncovering-the-Structural-Fairness-in-Graph-Contrastive-Learning
  Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"
  ☆26Updated last year
• kaize0409 / S-3-CL
  PyTorch Implementation for "Eliciting Structural and Semantic Global Knowledge in Unsupervised Graph Contrastive Learning" (AAAI2023)
  ☆21Updated last year
• SitaoLuan / ACM-GNN
  NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…
  ☆68Updated 11 months ago
• yuwvandy / FairVGNN
  ☆24Updated 2 years ago
• sktsherlock / TAG-Benchmark
  Benchmark
  ☆70Updated 5 months ago
• Nashchou / MultiGPrompt
  ☆14Updated 7 months ago
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆23Updated 3 months ago
• JiaruiFeng / TAGLAS
  An atlas of text-attributed graph datasets in the era of large graph and language model.
  ☆14Updated this week
• yongduosui / AIA
  [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…
  ☆13Updated 10 months ago
• YuanchenBei / Awesome-Graph-Structure-Learning
  A curated list of papers on graph structure learning (GSL).
  ☆28Updated 2 months ago
• MingChen-Sun / GPPT
  ☆53Updated last year
• yixinliu233 / D2PT
  [KDD'23] Learning Strong Graph Neural Networks with Weak Information
  ☆42Updated last year
• rollingstonezz / Curriculum_learning_for_GNNs
  This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"
  ☆13Updated 10 months ago
• yixinliu233 / G-OOD-D
  [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection
  ☆33Updated last year
• bigheiniu / GRENADE
  GRENADE: Graph-Centric Language Model for Self-Supervised Representation Learning on Text-Attributed Graphs
  ☆10Updated 5 months ago
• Leirunlin / EvenNet
  Pytorch implementation of EvenNet.
  ☆17Updated last year