Parameterized Explainer for Graph Neural Network
☆144Feb 23, 2024Updated 2 years ago
Alternatives and similar repositories for PGExplainer
Users that are interested in PGExplainer are comparing it to the libraries listed below
Sorting:
- Generating PGM Explanation for GNN predictions☆75Jul 6, 2023Updated 2 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆69Feb 16, 2025Updated last year
- ☆58Mar 22, 2022Updated 3 years ago
- gnn explainer☆1,036Aug 30, 2024Updated last year
- Papers about explainability of GNNs☆795Mar 5, 2026Updated 2 weeks ago
- This is a Pytorch implementation of GraphLIME☆95Jan 6, 2022Updated 4 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆174Feb 19, 2024Updated 2 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆66Apr 7, 2022Updated 3 years ago
- ☆19Sep 30, 2022Updated 3 years ago
- GraphFramEx: a systematic evaluation framework for explainability methods on GNNs☆50Apr 8, 2024Updated last year
- Code for "Explainability methods for graph convolutional neural networks" - PE Pope*, S Kolouri*, M Rostami, CE Martin, H Hoffmann (CVPR …☆34Oct 29, 2025Updated 4 months ago
- ☆67Dec 19, 2025Updated 3 months ago
- ☆58Sep 28, 2022Updated 3 years ago
- ☆20Jul 30, 2024Updated last year
- A library for graph deep learning research☆2,002Jul 15, 2024Updated last year
- Explainability techniques for Graph Networks, applied to a synthetic dataset and an organic chemistry task. Code for the workshop paper "…☆127Nov 12, 2019Updated 6 years ago
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆132Jul 15, 2023Updated 2 years ago
- 一个XGNN实现过程☆12Apr 20, 2021Updated 4 years ago
- GraphXAI: Resource to support the development and evaluation of GNN explainers☆207May 22, 2024Updated last year
- Variational Graph Convolutional Networks☆23Oct 16, 2020Updated 5 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆121Aug 28, 2023Updated 2 years ago
- a robust metric (robust fidelity) for XGNN (ICLR24)☆12Jun 3, 2025Updated 9 months ago
- [ICML 2024] Code for Pairwise Alignment Improves Graph Domain Adaptation (Pair-Align)☆14Jun 15, 2024Updated last year
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Nov 24, 2022Updated 3 years ago
- ☆10Jun 14, 2025Updated 9 months ago
- Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022☆41Jun 13, 2022Updated 3 years ago
- GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020☆333Jul 6, 2023Updated 2 years ago
- GNNExplainer implementation using DGL☆31Mar 10, 2021Updated 5 years ago
- Learning to Drop: Robust Graph Neural Network via Topological Denoising & Robust Graph Representation Learning via Neural Sparsification☆82Apr 29, 2021Updated 4 years ago
- [ICML 2021] "Graph Contrastive Learning Automated" by Yuning You, Tianlong Chen, Yang Shen, Zhangyang Wang; [WSDM 2022] "Bringing Yo…☆116Sep 9, 2024Updated last year
- [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang…☆625Jul 17, 2024Updated last year
- Global Counterfactual Explainer for Graph Neural Networks☆22Mar 24, 2023Updated 2 years ago
- [The Web Conference 2024] GNNShap: Scalable and Accurate GNN Explanation using Shapley Values☆42Mar 5, 2024Updated 2 years ago
- ☆14Mar 4, 2022Updated 4 years ago
- A curated list of resources for OOD detection with graph data.☆19Dec 30, 2023Updated 2 years ago
- Extending the Neural Graph Algorithm Executor☆13Dec 8, 2022Updated 3 years ago
- ☆11Jul 12, 2022Updated 3 years ago
- [Preprint] Graph State Space Convolution (GSSC)☆14Jun 11, 2024Updated last year
- Explanation method for Graph Neural Networks (GNNs)☆71Apr 27, 2025Updated 10 months ago