List of Molecular and Material design using Generative AI and Deep Learning

[IJCAI 2023 survey track]A curated list of resources for chemical pre-trained models

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

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

List of molecules (small molecules, RNA, peptide, protein, enzymes, antibody, and PPIs) conformations and molecular dynamics (force fields) using generative artificial intelligence and deep learning

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

3D Graph Neural Networks for RGBD Semantic Segmentation

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.

A Survey of Learning from Graphs with Heterophily

(WWW 2021) Source code of PC-GNN

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

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

Awesome De novo drugs design papers

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

[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.

Edge-Augmented Graph Transformer

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.

GNNs in Recommendation Systems

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

MatTen: Equivariant Graph Neural Nets for Tensorial Properties of Materials