A collection of AWESOME things about Graph-Related LLMs.

A professional list on Large (Language) Models and Foundation Models (LLM, LM, FM) for Time Series, Spatiotemporal, and Event Data.

PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

Data for the paper "Simplicial closure and higher-order link prediction"

Standardized higher-order datasets with corresponding datasheets

DPPIN: A Biological Repository of Dynamic Protein-Protein Interaction Network Data, IEEE BigData 2022

Temporal Graph Benchmark project repo

This repository contains the code to reproduce experiments presented in the paper "Path Neural Networks: Expressive and Accurate Graph Neural Networks" (ICML 2023).

Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

Everything Evolves in Personalized PageRank, WWW 2023

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.

A Deep Graph-based Toolbox for Fraud Detection

This codebase is the official implementation of Test-Time Classifier Adjustment Module for Model-Agnostic Domain Generalization (NeurIPS2021, Spotlight)

DomainBed is a suite to test domain generalization algorithms

Fast and Easy Infinite Neural Networks in Python

[NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs"

Pytorch Implementation of DeepLog.

A Python Library for Graph Outlier Detection (Anomaly Detection)

Source code for HAKG: Hierarchy-Aware Knowledge Gated Network for Recommendation. SIGIR 2022.

PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"

upstream mirror

Python package built to ease deep learning on graph, on top of existing DL frameworks.

In-Memory Subgraph Matching: An In-depth Study by Dr. Shixuan Sun and Prof. Qiong Luo

Papers for database systems powered by artificial intelligence (machine learning for database)

[TPAMI-2018] A C++ framework for training/testing Support Vector Machine with Gaussian Sample Uncertainty (SVM-GSU).