YangLing0818 / GraphOODLinks
The official Implementation for TKDE paper "Individual and Structural Graph Information Bottlenecks for Out-of-Distribution Generalization"
☆14Updated 2 years ago
Alternatives and similar repositories for GraphOOD
Users that are interested in GraphOOD are comparing it to the libraries listed below
Sorting:
- Official implementation of GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs☆57Updated 8 months ago
- [NeurIPS 2023] Does Invariant Graph Learning via Environment Augmentation Learn Invariance?☆22Updated last year
- Official implementation of MARIO: Model Agnostic Recipe for Improving OOD Generalization of Graph Contrastive Learning☆19Updated last year
- [ICML 2022] Local Augmentation for Graph Neural Networks☆65Updated last year
- The implementation of "Joint Learning of Label and Environment Causal Independence for Graph Out-of-Distribution Generalization" (NeurIPS…☆22Updated last year
- [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Y…☆61Updated 3 years ago
- [ICLR 2024] VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs☆102Updated last year
- The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".☆33Updated 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
- PyTorch implementation of GraphGLOW: Universal and Generalizable Structure Learning for Graph Neural Networks☆36Updated 2 years ago
- [ICML 2024] How Interpretable Are Interpretable Graph Neural Networks?☆15Updated last year
- [NeurIPS 2022] Learning Causally Invariant Representations for Out-of-Distribution Generalization on Graphs☆117Updated 2 years ago
- [KDD 2022] Implementation of "Feature Overcorrelation in Deep Graph Neural Networks: A New Perspective"☆45Updated last year
- [ICLR'23] Implementation of "Empowering Graph Representation Learning with Test-Time Graph Transformation"☆64Updated 2 years ago
- (ICLR 2022) Discovering Invariant Rationales for Graph Neural Networks☆133Updated 2 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆44Updated 2 years ago
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆37Updated 2 years ago
- NeurIPS2022-Debiasing Graph Neural Networks via Learning Disentangled Causal Substructure☆42Updated 2 years ago
- Official PyTorch implementation for the following KDD2022 paper: Variational Inference for Training Graph Neural Networks in Low-Data Re…☆20Updated 3 years ago
- Official Code Repository for the paper "Edge Representation Learning with Hypergraphs" (NeurIPS 2021)☆53Updated 2 years ago
- the code of MoG☆19Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆35Updated 2 years ago
- Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Cont…☆24Updated 2 years ago
- The official implementation for ICLR23 paper "GNNSafe: Energy-based Out-of-Distribution Detection for Graph Neural Networks"☆83Updated 2 years ago
- A generative one-for-all model for joint graph language modeling☆44Updated 4 months ago
- Codes for 'From Canonical Correlation Analysis to Self-supervised Graph Neural Networks'. https://arxiv.org/abs/2106.12484☆70Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆45Updated 3 years ago
- PyTorch Implementation for "Meta Propagation Networks for Graph Few-shot Semi-supervised Learning" (AAAI2022)☆29Updated 3 years ago
- A collection of papers and resources about Data Centric Graph Machine Learning (DC-GML)☆40Updated 2 years ago