Stars
Code for "MGCVAE: Multi-Objective Inverse Design via Molecular Graph Conditional Variational Autoencoder" (https://doi.org/10.1021/acs.jcim.2c00487)
Explanation by Progressive Exaggeration
Code for the paper "Brain Connectivity based Graph Convolutional Networks for Infant Age Prediction"
Generative adversarial network for normalizing and predicting time-dependent graphs with respect to a fixed template.
A Deep Graph Neural Network Architecture for Modelling Spatio-temporal Dynamics in rs-fMRI Data
repository for scripts used in UK BioBank analyses
The official implementation of our IPMI 2023 paper "SADM: Sequence-Aware Diffusion Model for Longitudinal Medical Image Generation"
STAGIN: Spatio-Temporal Attention Graph Isomorphism Network
Public facing notes page
Self-supervised Longitudinal Neighbourhood Embedding (LNE), MICCAI2021 & Speicial Issue on Medical Image Analysis
Benchmarks for Graph Machine Learning in Brain Connectomics
Enabling easy statistical significance testing for deep neural networks.
The official implementation for ICLR23 spotlight paper "DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion"
Improving autism identification with multisite data via site-dependence minimisation and second-order functional connectivity (TMI, 2022)
Graph Diffusion Convolution, as proposed in "Diffusion Improves Graph Learning" (NeurIPS 2019)
MICCAI 2022 paper
this project is for PMRID's training and testing
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
Predicting multigraph brain population from a single graph
Federated time-dependent graph evolution prediction with missing timepoints.
deep learning for image processing including classification and object-detection etc.
EvoGraphNet for graph time-series forecasting from a single timepoint.
A review of papers proposing novel GNN methods with application to brain connectivity published in 2017-2020.
Pytorch implementation of pooling-regularized GNN (PRGNN) for fMRI analysis. https://arxiv.org/pdf/2007.14589.pdf