(ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks
☆132Jul 15, 2023Updated 2 years ago
Alternatives and similar repositories for DIR-GNN
Users that are interested in DIR-GNN are comparing it to the libraries listed below. We may earn a commission when you buy through links labeled 'Ad' on this page.
Sorting:
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆121Aug 28, 2023Updated 2 years ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆207Feb 21, 2025Updated last year
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Nov 6, 2023Updated 2 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆46Nov 13, 2023Updated 2 years ago
- Official code for the CVPR 2022 (oral) paper "OrphicX: A Causality-Inspired Latent Variable Model for Interpreting Graph Neural Networks.…☆35Apr 2, 2022Updated 3 years ago
- GPU virtual machines on DigitalOcean Gradient AI • AdGet to production fast with high-performance AMD and NVIDIA GPUs you can spin up in seconds. The definition of operational simplicity.
- Code for Mind the Label Shift of Augmentation-based Graph OOD generalization (LiSA) in CVPR 2023. LiSA is a model-agnostic Graph OOD fram…☆16Jun 24, 2023Updated 2 years ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆97Nov 16, 2023Updated 2 years ago
- Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022☆41Jun 13, 2022Updated 3 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆92Nov 24, 2022Updated 3 years ago
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆22Nov 4, 2024Updated last year
- Ratioanle-aware Graph Contrastive Learning codebase☆44Jun 15, 2023Updated 2 years ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆174Feb 19, 2024Updated 2 years ago
- [KDD'22] Source codes of "Graph Rationalization with Environment-based Augmentations"☆47Mar 27, 2025Updated last year
- We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NU…☆516Mar 3, 2023Updated 3 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- Papers about explainability of GNNs☆796Mar 5, 2026Updated 3 weeks ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆54Apr 12, 2024Updated last year
- Papers about out-of-distribution generalization on graphs.☆168Jun 5, 2023Updated 2 years ago
- Parameterized Explainer for Graph Neural Network☆144Feb 23, 2024Updated 2 years ago
- (ICML 2023) Discover and Cure: Concept-aware Mitigation of Spurious Correlation☆45Nov 17, 2025Updated 4 months ago
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆23Aug 25, 2024Updated last year
- Official code of "Invariant Collaborative Filtering to Popularity Distribution Shift" (2023 WWW)☆21Jul 27, 2023Updated 2 years ago
- Author: Tong Zhao (tzhao2@nd.edu). ICML 2022. Learning from Counterfactual Links for Link Prediction☆71Aug 10, 2022Updated 3 years ago
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆69Feb 16, 2025Updated last year
- 1-Click AI Models by DigitalOcean Gradient • AdDeploy popular AI models on DigitalOcean Gradient GPU virtual machines with just a single click and start building anything your business needs.
- [WWW2024 Oral] "Graph Out-of-Distribution Generalization via Causal Intervention”.☆27Oct 23, 2024Updated last year
- ☆11Mar 8, 2024Updated 2 years ago
- Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions☆12Mar 26, 2020Updated 6 years ago
- [ICML2024] Learning Divergence Fields for Shift-Robust Graph Representations☆11Aug 15, 2024Updated last year
- A list of Graph Causal Learning materials.☆211Jan 24, 2025Updated last year
- New structural distributional shifts for evaluating graph models☆16Oct 25, 2023Updated 2 years ago
- A Flexible Generative Framework for Graph-based Semi-supervised Learning (NeurIPS 2019)☆16Nov 14, 2021Updated 4 years ago
- Official code of "Incorporating Bias-aware Margins into Contrastive Loss for Collaborative Filtering" (2022 NeurIPS)☆21May 19, 2023Updated 2 years ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆38May 6, 2022Updated 3 years ago
- Virtual machines for every use case on DigitalOcean • AdGet dependable uptime with 99.99% SLA, simple security tools, and predictable monthly pricing with DigitalOcean's virtual machines, called Droplets.
- this is a work about UpliftRec☆10Dec 10, 2024Updated last year
- ☆45Feb 14, 2024Updated 2 years ago
- [ICML 2023] Structural Re-weighting Improves Graph Domain Adaptation (StruRW)☆22Jun 20, 2023Updated 2 years ago
- Size-Invariant Graph Representations for Graph Classification Extrapolations (ICML 2021 Long Talk)☆22Jan 26, 2023Updated 3 years ago
- Code for Environment Inference for Invariant Learning (ICML 2021 Paper)☆51Jun 10, 2021Updated 4 years ago
- [CIKM 2023] Towards Fair Graph Neural Networks via Graph Counterfactual.☆14Mar 4, 2025Updated last year
- ☆58Sep 28, 2022Updated 3 years ago