12wang3 / rrlLinks
The code of NeurIPS 2021 paper "Scalable Rule-Based Representation Learning for Interpretable Classification" and TPAMI paper "Learning Interpretable Rules for Scalable Data Representation and Classification"
☆120Updated last year
Alternatives and similar repositories for rrl
Users that are interested in rrl are comparing it to the libraries listed below
Sorting:
- ☆45Updated last year
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆131Updated 2 years ago
- NeurIPS'22 | TransTab: Learning Transferable Tabular Transformers Across Tables☆203Updated 9 months ago
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 3 years ago
- ☆40Updated 2 years ago
- ☆51Updated 4 years ago
- Code to reproduce the results in the paper Supervised Learning on Relational Databases with Graph Neural Networks.☆63Updated 5 years ago
- Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)☆42Updated 3 years ago
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆120Updated 2 years ago
- Reinforced Causal Explainer for Graph Neural Networks, TPAMI2022☆40Updated 3 years ago
- Official code for the ICML 2021 paper "Generative Causal Explanations for Graph Neural Networks."☆67Updated 3 years ago
- List of Publications in Graph Contrastive Learning☆34Updated 3 years ago
- "Shift-Robust GNNs: Overcoming the Limitations of Localized Graph Training Data" (NeurIPS 21')☆49Updated 3 years ago
- The official code of WWW2021 paper: Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation …☆77Updated 4 years ago
- Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization (NeurIPS 21')☆23Updated 4 years ago
- Rethinking Graph Regularization for Graph Neural Networks (AAAI2021)☆34Updated 4 years ago
- A list of Graph Causal Learning materials.☆208Updated 11 months ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆97Updated 2 years ago
- ☆97Updated last year
- Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 2021) + Pytorch Implementation of GNN attribution methods☆70Updated 10 months ago
- ☆173Updated last year
- This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?☆22Updated 3 years ago
- This repository contains the implementation of SimplEx, a method to explain the latent representations of black-box models with the help …☆25Updated 2 years ago
- Pytorch implementation of differentiable group normalization (NeurIPS 2020)☆38Updated 5 years ago
- WSDM2022 Challenge - Large scale temporal graph link prediction☆38Updated 3 years ago
- ☆23Updated 2 years ago
- PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"☆89Updated 4 years ago
- ☆28Updated 2 years ago
- AutoGCL: Automated Graph Contrastive Learning via Learnable View Generators (AAAI 2022)☆48Updated 3 years ago
- ☆67Updated 2 years ago