b'Islem Rekik'

research

∙ 12/14/2022

Population Template-Based Brain Graph Augmentation for Improving One-Shot Learning Classification

The challenges of collecting medical data on neurological disorder diagn...

0 Oben Özgür, et al. ∙

research

∙ 12/09/2022

Predicting Shape Development: a Riemannian Method

Predicting the future development of an anatomical shape from a single b...

0 Doğa Türkseven, et al. ∙

research

∙ 09/13/2022

Investigating the Predictive Reproducibility of Federated Graph Neural Networks using Medical Datasets

Graph neural networks (GNNs) have achieved extraordinary enhancements in...

0 Mehmet Yigit Balik, et al. ∙

research

∙ 09/13/2022

Predicting Brain Multigraph Population From a Single Graph Template for Boosting One-Shot Classification

A central challenge in training one-shot learning models is the limited ...

0 Furkan Pala, et al. ∙

research

∙ 04/05/2022

Comparative Survey of Multigraph Integration Methods for Holistic Brain Connectivity Mapping

One of the greatest scientific challenges in network neuroscience is to ...

0 Nada Chaari, et al. ∙

research

∙ 03/26/2022

Contrastive Graph Learning for Population-based fMRI Classification

Contrastive self-supervised learning has recently benefited fMRI classif...

0 Xuesong Wang, et al. ∙

research

∙ 10/06/2021

Recurrent Multigraph Integrator Network for Predicting the Evolution of Population-Driven Brain Connectivity Templates

Learning how to estimate a connectional brain template(CBT) from a popul...

0 Oytun Demirbilek, et al. ∙

research

∙ 10/06/2021

StairwayGraphNet for Inter- and Intra-modality Multi-resolution Brain Graph Alignment and Synthesis

Synthesizing multimodality medical data provides complementary knowledge...

0 Islem Mhiri, et al. ∙

research

∙ 10/06/2021

Inter-Domain Alignment for Predicting High-Resolution Brain Networks Using Teacher-Student Learning

Accurate and automated super-resolution image synthesis is highly desire...

17 Basar Demir, et al. ∙

research

∙ 10/06/2021

One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction

Few-shot learning presents a challenging paradigm for training discrimin...

0 Umut Guvercin, et al. ∙

research

∙ 10/06/2021

A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint

Charting the baby connectome evolution trajectory during the first year ...

10 Alaa Bessadok, et al. ∙

research

∙ 09/16/2021

A Comparative Study of Machine Learning Methods for Predicting the Evolution of Brain Connectivity from a Baseline Timepoint

Predicting the evolution of the brain network, also called connectome, b...

8 Şeymanur Aktı, et al. ∙

research

∙ 09/06/2021

Quantifying the Reproducibility of Graph Neural Networks using Multigraph Brain Data

Graph neural networks (GNNs) have witnessed an unprecedented proliferati...

0 Mohammed Amine Gharsallaoui, et al. ∙

research

∙ 06/17/2021

Predicting cognitive scores with graph neural networks through sample selection learning

Analyzing the relation between intelligence and neural activity is of th...

0 Martin Hanik, et al. ∙

research

∙ 06/07/2021

Graph Neural Networks in Network Neuroscience

Noninvasive medical neuroimaging has yielded many discoveries about the ...

30 Alaa Bessadok, et al. ∙

research

∙ 05/06/2021

Brain Multigraph Prediction using Topology-Aware Adversarial Graph Neural Network

Brain graphs (i.e, connectomes) constructed from medical scans such as m...

13 Alaa Bessadok, et al. ∙

research

∙ 05/02/2021

Brain Graph Super-Resolution Using Adversarial Graph Neural Network with Application to Functional Brain Connectivity

Brain image analysis has advanced substantially in recent years with the...

0 Megi Isallari, et al. ∙

research

∙ 12/28/2020

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

A connectional brain template (CBT) is a normalized graph-based represen...

0 Mustafa Burak Gurbuz, et al. ∙

research

∙ 09/28/2020

Deep EvoGraphNet Architecture For Time-Dependent Brain Graph Data Synthesis From a Single Timepoint

Learning how to predict the brain connectome (i.e. graph) development an...

10 Ahmed Nebli, et al. ∙

research

∙ 09/24/2020

Multi-View Brain HyperConnectome AutoEncoder For Brain State Classification

Graph embedding is a powerful method to represent graph neurological dat...

0 Alin Banka, et al. ∙

research

∙ 09/24/2020

Multi-Scale Profiling of Brain Multigraphs by Eigen-based Cross-Diffusion and Heat Tracing for Brain State Profiling

The individual brain can be viewed as a highly-complex multigraph (i.e. ...

0 Mustafa Saglam, et al. ∙

research

∙ 09/24/2020

Adversarial Brain Multiplex Prediction From a Single Network for High-Order Connectional Gender-Specific Brain Mapping

Brain connectivity networks, derived from magnetic resonance imaging (MR...

0 Ahmed Nebli, et al. ∙

research

∙ 09/23/2020

Foreseeing Brain Graph Evolution Over Time Using Deep Adversarial Network Normalizer

Foreseeing the brain evolution as a complex highly inter-connected syste...

0 Zeynep Gurler, et al. ∙

research

∙ 09/23/2020

Residual Embedding Similarity-Based Network Selection for Predicting Brain Network Evolution Trajectory from a Single Observation

While existing predictive frameworks are able to handle Euclidean struct...

0 Ahmet Serkan Goktas, et al. ∙

research

∙ 09/23/2020

GSR-Net: Graph Super-Resolution Network for Predicting High-Resolution from Low-Resolution Functional Brain Connectomes

Catchy but rigorous deep learning architectures were tailored for image ...

0 Megi Isallari, et al. ∙

research

∙ 09/23/2020

Topology-Aware Generative Adversarial Network for Joint Prediction of Multiple Brain Graphs from a Single Brain Graph

Several works based on Generative Adversarial Networks (GAN) have been r...

0 Alaa Bessadok, et al. ∙

research

∙ 09/23/2020

Supervised Multi-topology Network Cross-diffusion for Population-driven Brain Network Atlas Estimation

Estimating a representative and discriminative brain network atlas (BNA)...

0 Islem Mhiri, et al. ∙

research

∙ 08/30/2020

Deep Hypergraph U-Net for Brain Graph Embedding and Classification

-Background. Network neuroscience examines the brain as a complex system...

0 Mert Lostar, et al. ∙

research

∙ 04/28/2020

Machine Learning Methods for Brain Network Classification: Application to Autism Diagnosis using Cortical Morphological Networks

Autism spectrum disorder (ASD) affects the brain connectivity at differe...

0 Ismail Bilgen, et al. ∙

research

∙ 07/13/2019

Image Evolution Trajectory Prediction and Classification from Baseline using Learning-based Patch Atlas Selection for Early Diagnosis

Patients initially diagnosed with early mild cognitive impairment (eMCI)...

1 Can Gafuroglu, et al. ∙

research

∙ 08/06/2018

A Review on Image- and Network-based Brain Data Analysis Techniques for Alzheimer's Disease Diagnosis Reveals a Gap in Developing Predictive Methods for Prognosis

Unveiling pathological brain changes associated with Alzheimer's disease...

0 Mayssa Soussia, et al. ∙

research

∙ 09/05/2017

Dynamic Multiscale Tree Learning Using Ensemble Strong Classifiers for Multi-label Segmentation of Medical Images with Lesions

We introduce a dynamic multiscale tree (DMT) architecture that learns ho...

0 Samya Amiri, et al. ∙

Islem Rekik

Featured Co-authors