isail-laboratory / iDEA-iSAIL-Reading-Group

Related projects ⓘ

Alternatives and complementary repositories for iDEA-iSAIL-Reading-Group

• davidchouzdw / iDEA-iSAIL-Reading-Group
  ☆2Updated 3 years ago
• yushundong / EDITS
  Open source code for paper "EDITS: Modeling and Mitigating Data Bias for Graph Neural Networks".
  ☆26Updated 2 years ago
• yushundong / PyGDebias
  Open-source Library PyGDebias: Graph Datasets and Fairness-Aware Graph Mining Algorithms
  ☆60Updated 6 months ago
• yushundong / Graph-Mining-Fairness-Data
  Open-source datasets for paper "Fairness in Graph Mining: A Survey".
  ☆17Updated 2 years ago
• EnyanDai / FairGNN
  A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Informati…
  ☆57Updated last year
• EdisonLeeeee / Awesome-Fair-Graph-Learning
  Paper List for Fair Graph Learning (FairGL).
  ☆132Updated 2 months ago
• jma712 / GEAR
  ☆18Updated 2 years ago
• EnyanDai / RSGNN
  An official PyTorch implementation of "Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels" (WSDM 2022))
  ☆32Updated 2 years ago
• chirag-agarwall / nifty
  Code for paper https://arxiv.org/abs/2102.13186
  ☆39Updated 3 years ago
• ahxt / G2R
  [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction
  ☆26Updated 2 years ago
• zjs123 / DTGB
  Comprehensive Benchmark Dataset for Dynamic Text-Attributed Graphs
  ☆24Updated 2 weeks ago
• Juanhui28 / HeaRT
  ☆44Updated last month
• QueuQ / CGLB
  ☆50Updated last week
• qitianwu / GraphOOD-EERM
  The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"
  ☆82Updated 2 years ago
• CurryTang / LLM4Graph
  Ongoing project: a library for graph foundation model
  ☆13Updated 9 months ago
• likuanppd / STABLE
  source code of KDD 2022 paper "Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN".
  ☆27Updated 5 months ago
• CUAI / Non-Homophily-Benchmarks
  [WWW 2021 GLB] New Benchmarks for Learning on Non-Homophilous Graphs
  ☆111Updated 3 years ago
• yongduosui / AIA
  [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…
  ☆16Updated last year
• RecklessRonan / GloGNN
  ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily
  ☆42Updated 2 years ago
• jma712 / GraphCFE
  ☆15Updated 9 months ago
• blacksingular / wsdm_GDN
  [WSDM 2023] "Alleviating Structrual Distribution Shift in Graph Anomaly Detection" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, H…
  ☆20Updated last year
• yuwvandy / FairVGNN
  ☆24Updated 2 years ago
• GemsLab / HeteRobust
  How does Heterophily Impact the Robustness of Graph Neural Networks? Theoretical Connections and Practical Implications (KDD'22)
  ☆12Updated 2 years ago
• ahxt / g-mixup
  [ICML2022] G-Mixup: Graph Data Augmentation for Graph Classification
  ☆91Updated 8 months ago
• GemsLab / CPGNN
  ☆28Updated 3 years ago
• AiRyunn / BoT
  Implementation of "Bag of Tricks for Node Classification with Graph Neural Networks" based on DGL
  ☆35Updated last year
• flyingdoog / PTDNet
  Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification
  ☆74Updated 3 years ago
• yixinliu233 / GREET
  [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating
  ☆49Updated 2 years ago
• zepengzhang / awesome-graph-structure-learning
  A collection of papers on Graph Structural Learning (GSL)
  ☆52Updated 10 months ago
• thupchnsky / sgc_unlearn
  Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)
  ☆19Updated last year