Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates

28 December 2020

Papers citing "Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates"

8 / 8 papers shown

Title
Metadata-Driven Federated Learning of Connectional Brain Templates in Non-IID Multi-Domain Scenarios Geng Chen Qingyue Wang I. Rekik 28 0 0 14 Mar 2024
Population Template-Based Brain Graph Augmentation for Improving One-Shot Learning Classification Oben Özgür Arwa Rekik I. Rekik MedIm 20 0 0 14 Dec 2022
Deep Cross-Modality and Resolution Graph Integration for Universal Brain Connectivity Mapping and Augmentation Ece Cinar Sinem Elif Haseki Alaa Bessadok I. Rekik 16 2 0 13 Sep 2022
Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification Furkan Pala I. Rekik 24 2 0 13 Sep 2022
Federated Graph Machine Learning: A Survey of Concepts, Techniques, and Applications Xingbo Fu Binchi Zhang Yushun Dong Chen Chen Jundong Li FedML OOD AI4CE 26 35 0 24 Jul 2022
Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates Oytun Demirbilek I. Rekik 34 5 0 06 Oct 2021
One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction Umut Guvercin Mohammed Amine Gharsallaoui I. Rekik 27 6 0 06 Oct 2021
Brain Multigraph Prediction using Topology-Aware Adversarial Graph Neural Network Alaa Bessadok Mohamed Ali Mahjoub I. Rekik MedIm AI4CE 6 16 0 06 May 2021