Graph-in-Graph (GiG): Learning interpretable latent graphs in
non-Euclidean domain for biological and healthcare applications

Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications

1 April 2022

Kamilia Mullakaeva

Seyed-Ahmad Ahmadi

Nassir Navab

Michael M. Bronstein

Papers citing "Graph-in-Graph (GiG): Learning interpretable latent graphs in non-Euclidean domain for biological and healthcare applications"

6 / 6 papers shown

Title
Heterogeneous Graph Structure Learning through the Lens of Data-generating Processes Keyue Jiang Bohan Tang Xiaowen Dong Laura Toni 41 0 0 11 Mar 2025
MM-GTUNets: Unified Multi-Modal Graph Deep Learning for Brain Disorders Prediction Luhui Cai Weiming Zeng Hongyu Chen Hua Zhang Yueyang Li Hongjie Yan Lingbin Bian Lingbin Bian Wai Ting Siok Nizhuan Wang MedIm 45 3 0 20 Jun 2024
Few-Shot Graph Learning for Molecular Property Prediction Zhichun Guo Chuxu Zhang W. Yu John E. Herr Olaf Wiest Meng-Long Jiang Nitesh V. Chawla AI4CE 106 168 0 16 Feb 2021
Deep Graph Normalizer: A Geometric Deep Learning Approach for Estimating Connectional Brain Templates Mustafa Burak Gurbuz I. Rekik 26 26 0 28 Dec 2020
Spatio-Temporal Graph Convolution for Resting-State fMRI Analysis S. Gadgil Qingyu Zhao A. Pfefferbaum E. Sullivan Ehsan Adeli K. Pohl 53 150 0 24 Mar 2020
Geometric deep learning on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 234 1,811 0 25 Nov 2016