YuanchenBei / Awesome-Graph-Transfer-Learning
A curated list of papers on graph transfer learning (GTL).
☆17Updated last year
Alternatives and similar repositories for Awesome-Graph-Transfer-Learning
Users that are interested in Awesome-Graph-Transfer-Learning are comparing it to the libraries listed below
Sorting:
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆22Updated last year
- A collection of papers on Graph Structural Learning (GSL)☆54Updated last year
- The official implement of SIGKDD'24 paper: ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphs☆28Updated 9 months ago
- The code Implementation of the paper “Universal Prompt Tuning for Graph Neural Networks”.☆30Updated last year
- NIPS 24: Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights☆43Updated 4 months ago
- GraphACL: Simple and Asymmetric Graph Contrastive Learning (NeurIPS 2023)☆32Updated 11 months ago
- The Open Source Code For ICML 2023 Paper "Finding the Missing-half: Graph Complementary Learning for Homophily-prone and Heterophily-pron…☆15Updated last year
- Official Code: TheWebConf 2022 Compact Graph Structure Learning via Mutual Information Compression☆24Updated last year
- ICML 2022, Finding Global Homophily in Graph Neural Networks When Meeting Heterophily☆43Updated 2 years ago
- Official implementation of 'All in One and One for All: A Simple yet Effective Method towards Cross-domain Graph Pretraining' published i…☆35Updated 6 months ago
- Code & data for ICLR'23 Spotlight paper "Learning MLPs on Graphs: A Unified View of Effectiveness, Robustness, and Efficiency".☆31Updated 2 years ago
- Ratioanle-aware Graph Contrastive Learning codebase☆43Updated last year
- [AAAI'23] Beyond Smoothing: Unsupervised Graph Representation Learning with Edge Heterophily Discriminating☆51Updated 2 years ago
- Open Source Code for GAugLLM: Improving Graph Contrastive Learning for Text-Attributed Graphs with Large Language Models (KDD'24)☆26Updated 10 months ago
- the code of MoG☆15Updated 9 months ago
- Resource for "A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based Perspective"☆30Updated last week
- Pytorch implementation of NeurIPS-23:"Structure-free Graph Condensation (SFGC): From Large-scale Graphs to Condensed Graph-free Data"☆30Updated last year
- [NeurIPS 2023] "Unleashing the Power of Graph Data Augmentation on Covariate Distribution Shift" by Yongduo Sui, Qitian Wu, Jiancan Wu, Q…☆17Updated last year
- NeurIPS 2022, Revisiting Heterophily For Graph Neural Networks, official PyTorch implementation for Adaptive Channel Mixing (ACM) GNN fra…☆81Updated 5 months ago
- Official Implementation of "D4Explainer: In-Distribution GNN Explanations via Discrete Denoising Diffusion"☆21Updated last year
- [KDD'23] Learning Strong Graph Neural Networks with Weak Information☆43Updated last year
- Papers about Graph Contrastive Learning and Graph Self-supervised Learning on Graphs with Heterophily☆37Updated last year
- Implementation Codes for NeurIPS22 paper "Dynamic Graph Neural Networks Under Spatio-Temporal Distribution Shift"☆20Updated 2 years ago
- ☆22Updated 7 months ago
- Official code implementation for WSDM 23 paper Graph Sequential Neural ODE Process for Link Prediction on Dynamic and Sparse Graphs.☆34Updated 2 years ago
- Source code for NeurIPS 2022 paper "Uncovering the Structural Fairness in Graph Contrastive Learning"☆29Updated 2 years ago
- [WSDM'23] GOOD-D: On Unsupervised Graph Out-Of-Distribution Detection☆40Updated 2 years ago
- The official implementation of the paper "Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing" (ICLR 2023).☆44Updated last year
- This is the official repository for NeurIPS 2023 paper "Curriculum Learning for Graph Neural Networks: Which Edges Should We Learn First"☆15Updated last year
- ☆15Updated last year