Stars
DHG-Bench is a comprehensive benchmark for Deep Hypergraph Learning
Relational Database Learning with Foundation Models
Graph Neural Network Library for PyTorch
Python package built to ease deep learning on graph, on top of existing DL frameworks.
Reconsidering the Performance of GAE in Link Prediction
[NeurIPS 2025 Datasets and Benchmarks] Source code for the paper RDB2G-Bench: A Comprehensive Benchmark for Automatic Graph Modeling of Relational Databases
PyGDA is a Python library for Graph Domain Adaptation
Community extensions for TabPFN - the foundation model for tabular data. Built with TabPFN! 🤗
An extremely fast Python package and project manager, written in Rust.
LimiX: Unleashing Structured-Data Modeling Capability for Generalist Intelligence https://arxiv.org/abs/2509.03505
GFT: Graph Foundation Model with Transferable Tree Vocabulary, NeurIPS 2024.
Official Repository of Adaptive Message Passing
GraphMAE: Self-Supervised Masked Graph Autoencoders in KDD'22
[ICML2024] "LLaGA: Large Language and Graph Assistant", Runjin Chen, Tong Zhao, Ajay Jaiswal, Neil Shah, Zhangyang Wang
[ICML 2025] Official Implementation of "Aggregation Buffer: Revisiting DropEdge with a New Parameter Block"
GraphAny: Fully-inductive Node Classification on Arbitrary Graphs
[ICLR 2025] Let Your Features Tell The Differences: Understanding Graph Convolution By Feature Splitting
A library for efficient similarity search and clustering of dense vectors.
[NeurIPS 2024] Implementation of "Classic GNNs are Strong Baselines: Reassessing GNNs for Node Classification"
Official repository for NeurIPS'23 paper: GraphPatcher: Mitigating Degree Bias for Graph Neural Networks via Test-time Augmentation
This is an official implementation of "NodeMixup: Tackling Under-Reaching for Graph Neural Networks" (AAAI 2024)