60 citations · 215 across the 55 of their papers we have counts for
10 papers · 1 filter
UnifiedFL: A Dynamic Unified Learning Framework for Equitable Federation
Furkan Pala, Islem Rekik
Federated learning (FL) has emerged as a key paradigm for collaborative model training across multiple clients without sharing raw data, enabling privacy-preserving applications in…
FireGNN: Neuro-Symbolic Graph Neural Networks with Trainable Fuzzy Rules for Interpretable Medical Image Classification
Prajit Sengupta, Islem Rekik
Medical image classification requires not only high predictive performance but also interpretability to ensure clinical trust and adoption. Graph Neural Networks (GNNs) offer a pow…
CogGNN: Cognitive Graph Neural Networks in Generative Connectomics
Mayssa Soussia, Yijun Lin, Mohamed Ali Mahjoub +1
Generative learning has advanced network neuroscience, enabling tasks like graph super-resolution, temporal graph prediction, and multimodal brain graph fusion. However, current me…
Multi-Sensory Cognitive Computing for Learning Population-level Brain Connectivity
Mayssa Soussia, Mohamed Ali Mahjoub, Islem Rekik
The generation of connectional brain templates (CBTs) has recently garnered significant attention for its potential to identify unique connectivity patterns shared across individua…
GNN-based Unified Deep Learning
Furkan Pala, Islem Rekik
Deep learning models often struggle to maintain generalizability in medical imaging, particularly under domain-fracture scenarios where distribution shifts arise from varying imagi…
X-Node: Self-Explanation is All We Need
Prajit Sengupta, Islem Rekik
Graph neural networks (GNNs) have achieved state-of-the-art results in computer vision and medical image classification tasks by capturing structural dependencies across data insta…
Multimodal Sheaf-based Network for Glioblastoma Molecular Subtype Prediction
Shekhnaz Idrissova, Islem Rekik
Glioblastoma is a highly invasive brain tumor with rapid progression rates. Recent studies have shown that glioblastoma molecular subtype classification serves as a significant bio…
NEURAL: Attention-Guided Pruning for Unified Multimodal Resource-Constrained Clinical Evaluation
Devvrat Joshi, Islem Rekik
The rapid growth of multimodal medical imaging data presents significant storage and transmission challenges, particularly in resource-constrained clinical settings. We propose NEU…
GraphTreeGen: Subtree-Centric Approach to Efficient and Supervised Graph Generation
Yitong Luo, Islem Rekik
Brain connectomes, representing neural connectivity as graphs, are crucial for understanding brain organization but costly and time-consuming to acquire, motivating generative appr…
Self-supervised Graph Transformer with Contrastive Learning for Brain Connectivity Analysis towards Improving Autism Detection
Yicheng Leng, Syed Muhammad Anwar, Islem Rekik +2
Functional Magnetic Resonance Imaging (fMRI) provides useful insights into the brain function both during task or rest. Representing fMRI data using correlation matrices is found t…