xiangwang1223 / reinforced_causal_explainer
Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
☆32Updated 2 years ago
Related projects ⓘ
Alternatives and complementary repositories for reinforced_causal_explainer
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆65Updated 2 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆54Updated last year
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆78Updated last year
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆38Updated last year
- Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.…☆34Updated 2 years ago
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆41Updated 2 years ago
- Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)☆120Updated last year
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 3 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 3 years ago
- Lifelong Learning of Graph Neural Networks for Open-World Node Classification☆28Updated last year
- ☆42Updated 9 months ago
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆31Updated 2 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆47Updated 2 years ago
- Source Code for ICML 2022 paper "Boosting Graph Structure Learning with Dummy Nodes"☆19Updated last year
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆44Updated 10 months ago
- Adaptive evaluation reveals that most examined adversarial defenses for GNNs show no or only marginal improvement in robustness. (NeurIPS…☆28Updated 2 years ago
- Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.☆33Updated last year
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 2 years ago
- Official PyTorch implementation for the following KDD2022 paper: Variational Inference for Training Graph Neural Networks in Low-Data Re…☆18Updated 2 years ago
- dynamic graph/network embedding/representation methods☆16Updated 4 years ago
- Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"☆17Updated last year
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆86Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆102Updated last year
- A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which appeared in …☆29Updated 2 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆18Updated 2 weeks ago
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆36Updated last year
- AAAI 2024 Accept☆13Updated 6 months ago
- The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021☆35Updated 2 years ago
- Variational Graph Convolutional Networks☆22Updated 4 years ago
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆50Updated 2 years ago