gnns 开源项目推荐（176 个）

ruvnet /RuVector

RuVector 提供高性能、实时决策与智能体记忆、自学习 AI，以及使用 Rust 构建的 Vector GNN DB。

AspirinCode /papers-for-molecular-design-using-DL

使用生成AI和深度学习进行分子和材料设计列表

junxia97 /awesome-pretrain-on-molecules

[IJCAI 2023 survey track] 化学预训练模型资源精选列表

CrawlScript /tf_geometric

Efficient and Friendly Graph Neural Network Library for TensorFlow 1.x and 2.x

chingyaoc /ggnn.pytorch

A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)

AspirinCode /awesome-AI4MolConformation-MD

使用生成性人工智能和深度学习的分子（小分子、RNA、肽、蛋白质、酶、抗体和PPI）的形态和分子动力学（力场）列表

basiralab /GNNs-in-Network-Neuroscience

A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.

yanx27 /3DGNN_pytorch

3D Graph Neural Networks for RGBD Semantic Segmentation

FedML-AI /FedGraphNN

FedGraphNN: A Federated Learning Platform for Graph Neural Networks with MLOps Support. The previous research version is accepted to ICLR'2021 - DPML and MLSys'21 - GNNSys workshops.

gongchenghua /Papers-Graphs-with-Heterophily

A Survey of Learning from Graphs with Heterophily

PonderLY /PC-GNN

(WWW 2021) Source code of PC-GNN

xmh1011 /AT-DGNN

[BIBM2024] MEEG and AT-DGNN: Improving EEG Emotion Recognition with Music Introducing and Graph-based Learning

tech-srl /bottleneck

Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"

asarigun /awesome-denovo-papers

Awesome De novo drugs design papers

Graphlet-AI /graphml-class

Full Stack Graph Machine Learning: Theory, Practice, Tools and Techniques

KuroginQin /OpenTLP

[ACM Computing Surveys'23] Implementations or refactor of some temporal link prediction/dynamic link prediction methods and summary of related open resources for survey paper "Temporal Link Prediction: A Unified Framework, Taxonomy, and Review" which has been accepted by ACM Computing Surveys.

USC-InfoLab /NeuroGNN

NeuroGNN is a state-of-the-art framework for precise seizure detection and classification from EEG data. It employs dynamic Graph Neural Networks (GNNs) to capture intricate spatial, temporal, semantic, and taxonomic correlations between EEG electrode locations and brain regions, resulting in improved accuracy. Presented at PAKDD '24.

shamim-hussain /egt

Edge-Augmented Graph Transformer

caio-freitas /GraphARM

An implementation of the Autoregressive Diffusion Model for Graph Generation from [Kong et al. 2023]

nianticlabs /relpose-gnn

[3DV21] Visual Camera Re-Localization Using Graph Neural Networks and Relative Pose Supervision, M. Türkoǧlu et al.