Alternatives and similar repositories for SGIR

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

• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆97Updated 2 years ago
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆44Updated 2 years ago
• junxia97 / SimGRACE
  [WWW 2022] "SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation"
  ☆81Updated 3 years ago
• SongtaoLiu0823 / LAGNN
  [ICML 2022] Local Augmentation for Graph Neural Networks
  ☆66Updated last year
• divelab / LECI
  The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…
  ☆22Updated last year
• zaixizhang / ProtGNN
  Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"
  ☆50Updated 3 years ago
• googlebaba / DisC
  NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
  ☆44Updated 2 years ago
• googlebaba / StableGNN
  StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs
  ☆26Updated 2 years ago
• yuwvandy / DPGNN
  ☆38Updated 2 years ago
• LFhase / CIGA
  [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
  ☆118Updated 2 years ago
• Samyu0304 / graph-information-bottleneck-for-Subgraph-Recognition
  ☆57Updated 3 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆57Updated last year
• DeepGraphLearning / GraphLoG
  Implementation of Self-supervised Graph-level Representation Learning with Local and Global Structure (ICML 2021).
  ☆80Updated 4 years ago
• Graph-COM / GSAT
  [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.
  ☆172Updated last year
• LFhase / GALA
  [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?
  ☆22Updated last year
• tengxiao1 / GraphACL
  GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)
  ☆34Updated last year
• yihongma / CILG-Papers
  A curated list of papers and code related to class-imbalanced learning on graphs (CILG).
  ☆43Updated 10 months ago
• kaize0409 / Meta-PN
  PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)
  ☆29Updated 3 years ago
• qitianwu / GraphOOD-GNNSafe
  The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"
  ☆84Updated 2 years ago
• LarsHoldijk / RE-ParameterizedExplainerForGraphNeuralNetworks
  ☆55Updated 3 years ago
• TrustAGI-Lab / MERIT
  [IJCAI 2021] A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning".
  ☆40Updated 3 years ago
• skepsun / Adaptive-Graph-Diffusion-Networks
  ☆50Updated last year
• Shen-Lab / GraphCL_Automated
  [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…
  ☆116Updated last year
• EdisonLeeeee / MaskGAE
  [KDD 2023] What’s Behind the Mask: Understanding Masked Graph Modeling for Graph Autoencoders
  ☆91Updated last year
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆105Updated last year
• kaize0409 / awesome-few-shot-gnn
  An index of algorithms for few-shot learning/meta-learning on graphs
  ☆155Updated 7 months ago
• Namkyeong / AFGRL
  The official source code for "Augmentation-Free Self-Supervised Learning on Graphs"
  ☆77Updated 3 years ago
• RManLuo / GSNOP
  Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.
  ☆34Updated 2 years ago
• ChandlerBang / GTrans
  [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"
  ☆65Updated 2 years ago
• yifeiacc / COSTA
  Code for KDD'22 paper, COSTA: Covariance-Preserving Feature Augmentation for Graph Contrastive Learning
  ☆49Updated 2 years ago