#Gnn
Showing 29 of 29 repositories tagged #gnn, ranked by stars
RuVector is a High Performance, Real-Time, Self-Learning Ai, Vector GNN, Memory DB built in Rust.
PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)
TensorFlow GNN is a library to build Graph Neural Networks on the TensorFlow platform.
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
A repository of pretty cool datasets that I collected for network science and machine learning research.
tsl: a PyTorch library for processing spatiotemporal data.
Computation-Efficient Era: A Comprehensive Survey of State Space Models in Medical Image Analysis
30 Semi-Supervised Learning Algorithms
Graph Neural Network based Social Recommendation Model. SIGIR2019.
A framework for building provenance-based intrusion detection systems with neural networks (KDD'26, USENIX Sec'25)
Readings for "A Unified View of Relational Deep Learning for Drug Pair Scoring." (IJCAI 2022)
PandaDock: Physics based Molecular Docking with GNN Scoring
Ant Graph Learning (AGL) provides a comprehensive solution for graph learning tasks at an industrial scale.
[ICLR 2022] Code for Graph-less Neural Networks: Teaching Old MLPs New Tricks via Distillation (GLNN)
This repository is used to collect papers and code in the field of AI.
RouteNet baseline for the Graph Neural Networking Challenge (https://bnn.upc.edu/challenge/)
πThe complete open-source release of the book γ Deep Learning: Foundations and Concepts γ and its related supporting resources
Edge-Augmented Graph Transformer
Gigantic Graph Learning (GiGL) Framework: Large-scale training and inference for Graph Neural Networks
Full Stack Graph Machine Learning: Theory, Practice, Tools and Techniques
Official implementation of GraphCLIP: Enhancing Transferability in Graph Foundation Models for Text-Attributed Graphs
Spatiotemporal datasets collected for network science, deep learning and general machine learning research.
The official PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf '21)
This repository houses the datasets/resources used in paper "ChatGPT Informed Graph Neural Network for Stock Movement Prediction". Dive in to find the datasets, code samples, and more!
Keras implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation". Includes synthetic GED data.
Graph Neural networks for NLP
A python implementation of Toward Vulnerability Detection for Ethereum Smart Contracts Using Graph-Matching Network.εΊδΊεΎη₯η»η½η»ηδ»₯ε€ͺεζΊθ½εηΊ¦ζΌζ΄ζ£ζ΅ζΉζ³η η©Ά
GRETEL is a framework for the development and evaluation of Counterfactual Explanation methods for Graph Classifiers
Implementation of AGDIFF: Attention-Enhanced Diffusion for Molecular Geometry Prediction