Alternatives and similar repositories for SimOAR_OAR

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

• yandex-research / structural-graph-shifts
  New structural distributional shifts for evaluating graph models
  ☆15Updated last year
• zknus / Graph-Diffusion-CDE
  Graph Neural Convection-Diffusion with Heterophily
  ☆11Updated 2 years ago
• wondergo2017 / DIDA
  Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"
  ☆22Updated 2 years ago
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆61Updated 2 years ago
• Graph-COM / Neural_Higher-order_Pattern_Prediction
  ☆14Updated 3 years ago
• Emiyalzn / GraphDE
  Official implementation for GraphDE: A Generative Framework for Debiased Learning and Out-of-Distribution Detection on Graphs (NeurIPS 20…
  ☆20Updated 2 years ago
• PKU-ML / G1
  ☆22Updated 3 months ago
• Amanda-Zheng / LEBED
  Pytorch implementation for ICLR24:"Online GNN Evaluation Under Test-Time Graph Distribution Shifts"
  ☆16Updated last year
• xiongbo010 / QGCN
  PyTorch implementation of Pseudo-Riemannian Graph Convolutional Networks (NeurIPS'22))
  ☆17Updated last year
• LFhase / GMT
  [ICML 2024] How Interpretable Are Interpretable Graph Neural Networks?
  ☆14Updated last year
• ventr1c / RES-GCL
  An official PyTorch implementation of "Certifiably Robust Graph Contrastive Learning" (NeurIPS 2023)
  ☆10Updated last year
• WtaoZhao / GraphGLOW
  PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks
  ☆36Updated 2 years ago
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆31Updated last year
• snap-stanford / prodigy
  ☆97Updated 2 years ago
• yushundong / Graph-Mining-Fairness-Data
  Open-source datasets for paper "Fairness in Graph Mining: A Survey".
  ☆18Updated 2 years ago
• devnkong / GOAT
  Official implementation of GOAT model (ICML2023)
  ☆38Updated 2 years ago
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆92Updated 2 years ago
• RingBDStack / GC-Bench
  An Open and Unified Benchmark for Graph Condensation (submitted to NeurIPS 2024 Datasets and Benchmarks Track)
  ☆19Updated last year
• yanweiyue / MoG
  the code of MoG
  ☆19Updated last year
• cshhzhao / GCOPE
  Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…
  ☆41Updated 10 months ago
• Graph-COM / StruRW
  [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)
  ☆21Updated 2 years ago
• jma712 / GEAR
  ☆18Updated 3 years ago
• liun-online / CoGSL
  Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression
  ☆24Updated last year
• ZhuYun97 / GraphCLIP
  Official implementation of GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs
  ☆53Updated 6 months ago
• AndrewZhou924 / Awesome-Graph-Prompting
  A curated list of resources for graph prompting methods
  ☆29Updated last year
• BUPT-GAMMA / CaGCN
  This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".
  ☆22Updated 3 years ago
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆44Updated 2 years ago
• googlebaba / DisC
  NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
  ☆41Updated last year
• snap-research / MLPInit-for-GNNs
  [ICLR 2023] MLPInit: Embarrassingly Simple GNN Training Acceleration with MLP Initialization
  ☆77Updated 2 years ago
• yushundong / PyGDebias
  Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms
  ☆63Updated last year