Alternatives and similar repositories for HyperSCI

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

• DM2-ND / CFLP
  Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction
  ☆70Updated 2 years ago
• Wuyxin / DIR-GNN
  Discovering Invariant Rationales for Graph Neural Networks (ICLR 2022)
  ☆130Updated 2 years ago
• yongduosui / CAL
  [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…
  ☆92Updated last year
• TimeLovercc / Awesome-Graph-Causal-Learning
  A list of Graph Causal Learning materials.
  ☆199Updated 6 months ago
• wanyu-lin / ICML2021-Gem
  Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."
  ☆67Updated 3 years ago
• nerdslab / bgrl
  PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)
  ☆80Updated last year
• LFhase / CIGA
  [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs
  ☆116Updated last year
• GemsLab / H2GCN
  Boost learning for GNNs from the graph structure under challenging heterophily settings. (NeurIPS'20)
  ☆104Updated last month
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆43Updated 4 years ago
• KimMeen / Neural-Temporal-Walks
  [NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dyna…
  ☆54Updated 2 years ago
• GentleZhu / Shift-Robust-GNNs
  "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')
  ☆48Updated 3 years ago
• BorealisAI / SLAPS-GNN
  PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
  ☆88Updated 3 years ago
• wokas36 / GraphSNN
  Graph Structured Neural Network
  ☆40Updated 2 years ago
• snap-stanford / GIB
  Graph Information Bottleneck (GIB) for learning minimal sufficient structural and feature information using GNNs
  ☆137Updated 2 years ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆106Updated last year
• flyingdoog / PGExplainer
  Parameterized Explainer for Graph Neural Network
  ☆137Updated last year
• rootlu / L2P-GNN
  Codes and datasets for AAAI-2021 paper "Learning to Pre-train Graph Neural Networks"
  ☆89Updated 4 years ago
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆91Updated 2 years ago
• xiangwang1223 / reinforced_causal_explainer
  Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
  ☆36Updated 3 years ago
• jindi-tju / U-GCN
  Source code of "NeurIPS21 - Universal Graph Convolutional Networks"
  ☆20Updated 3 years ago
• googlebaba / DisC
  NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure
  ☆41Updated last year
• susheels / adgcl
  Adversarial Graph Augmentation to Improve Graph Contrastive Learning
  ☆89Updated 3 years ago
• BUPT-GAMMA / Graph-Structure-Estimation-Neural-Networks
  Source code for WWW 2021 paper "Graph Structure Estimation Neural Networks"
  ☆58Updated 4 years ago
• bdy9527 / FAGCN
  ☆97Updated 4 years ago
• wondergo2017 / DIDA
  Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"
  ☆21Updated 2 years ago
• zpeng27 / GMI
  Graph Representation Learning via Graphical Mutual Information Maximization
  ☆117Updated 5 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
• kaize0409 / awesome-graph-data-augmentaion
  A curated list of publications and code about data augmentaion for graphs.
  ☆63Updated 3 years ago
• lsh0520 / RGCL
  Ratioanle-aware Graph Contrastive Learning codebase
  ☆44Updated 2 years ago
• jma712 / GraphCFE
  ☆17Updated 2 months ago