xiangwang1223 / reinforced_causal_explainerLinks
Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022
☆36Updated 3 years ago
Alternatives and similar repositories for reinforced_causal_explainer
Users that are interested in reinforced_causal_explainer are comparing it to the libraries listed below
Sorting:
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆92Updated last year
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆68Updated 3 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆88Updated 3 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆41Updated last year
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆53Updated 2 years ago
- Discovering Invariant Rationales for Graph Neural Networks (ICLR 2022)☆130Updated 2 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆116Updated last year
- [ICLR 2022] Implementation of paper "Automated Self-Supervised Learning for Graphs"☆42Updated 3 years ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆68Updated last year
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆89Updated last year
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 3 years ago
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆48Updated 3 years ago
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆60Updated 2 years ago
- The code for the ICML 2021 paper "Graph Neural Networks Inspired by Classical Iterative Algorithms".☆43Updated 4 years ago
- ☆77Updated 4 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆48Updated 3 years ago
- This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration".☆22Updated 3 years ago
- Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.…☆35Updated 3 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Updated 2 years ago
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 3 years ago
- The implementation of our NeurIPS 2020 paper "Graph Geometry Interaction Learning" (GIL)☆46Updated 4 years ago
- Official Implementation of AdaGCN (ICLR 2021)☆62Updated 3 years ago
- PyTorch implementation of BGRL (https://arxiv.org/abs/2102.06514)☆81Updated 2 years ago
- ☆46Updated last year
- [WWW2022] Geometric Graph Representation Learning via Maximizing Rate Reduction☆27Updated 3 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆21Updated 9 months ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆168Updated last year
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 4 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆37Updated 3 years ago