vduong143 / CAT-KDD-2024
Source code for the paper "CAT: Interpretable Concept-based Taylor Additive Models".
☆14Updated 2 months ago
Related projects ⓘ
Alternatives and complementary repositories for CAT-KDD-2024
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆101Updated last year
- Published papers focusing on graph domain adaptation☆31Updated 2 weeks ago
- An awesome collection of causality-inspired graph neural networks.☆47Updated 3 weeks ago
- [ICLR 2023, ICLR DG oral] PAIR, the optimizer and model selection criteria for OOD Generalization☆50Updated 7 months ago
- GitHub Repo for ICLR 2023 Paper "Temporal Domain Generalization with Drift-Aware Dynamic Neural Networks"☆54Updated last year
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆72Updated last year
- clone/download repositories from https://anonymous.4open.science/☆85Updated 2 years ago
- This is the official code repository for "Graph Neural Networks are Inherently Good Generalizers: Insights by Bridging GNNs and MLPs", wh…☆83Updated 5 months ago
- GOOD: A Graph Out-of-Distribution Benchmark [NeurIPS 2022 Datasets and Benchmarks]☆186Updated this week
- graph neural networks, information theory, AI for Sciences☆19Updated 2 years ago
- StableGNN-Generalizing Graph Neural Networks on Out-Of-Distribution Graphs☆19Updated last year
- Official implementation of AAAI'22 paper "ProtGNN: Towards Self-Explaining Graph Neural Networks"☆50Updated 2 years ago
- The official implementation for ICLR22 paper "Handling Distribution Shifts on Graphs: An Invariance Perspective"☆82Updated last year
- Official code of "Boosting Differentiable Causal Discovery via Adaptive Sample Reweighting" (2023 ICLR)☆16Updated last year
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆35Updated last year
- ☆60Updated last year
- ☆22Updated last year
- code for kdd feasibiiity☆9Updated last year
- The official implement of NeurIPS'24 Datasets and Benchmarks Track paper: GLBench: A Comprehensive Benchmark for Graphs with Large Langua…☆44Updated 2 weeks ago
- [KDD 2022] "Causal Attention for Interpretable and Generalizable Graph Classification" by Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, X…☆78Updated 11 months ago
- Code for "Graph Structure Learning with Variational Information Bottleneck" published in AAAI 2022☆32Updated 2 years ago
- A collection of papers and resources about Data-centric Graph Machine Learning (DC-GML).☆44Updated last year
- Learning Graphons via Structured Gromov-Wasserstein Barycenters☆22Updated 3 years ago
- Code for Mind the Label Shift of Augmentation-based Graph OOD generalization (LiSA) in CVPR 2023. LiSA is a model-agnostic Graph OOD fram…☆16Updated last year
- Official code of "Discovering Invariant Rationales for Graph Neural Networks" (ICLR 2022)☆120Updated last year
- A curated list of papers on graph structure learning (GSL).☆37Updated 4 months ago
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆16Updated last year
- Easily download anonymous Github repositories from https://anonymous.4open.science/ with a GUI interface☆95Updated 6 months ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆38Updated 11 months ago
- [ICML 2022] Graph Stochastic Attention (GSAT) for interpretable and generalizable graph learning.☆159Updated 8 months ago