Deep Clustering with a Dynamic Autoencoder. - Nairouz Mrabah; Naimul Mefraz Khan; Riadh Ksantini (CoRR, 2019)

Deep clustering with a Dynamic Autoencoder: From reconstruction towards centroids construction. - Nairouz Mrabah; Naimul Mefraz Khan; Riadh Ksantini; Zied Lachiri (Neural Networks, 2020)

Escaping Feature Twist: A Variational Graph Auto-Encoder for Node Clustering. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (IJCAI, 2022)

Adversarial Deep Embedded Clustering: On a Better Trade-off Between Feature Randomness and Feature Drift. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (IEEE Trans. Knowl. Data Eng., 2022)

Exploring the Interaction between Local and Global Latent Configurations for Clustering Single-Cell RNA-Seq: A Unified Perspective. - Nairouz Mrabah; Mohamed Mahmoud Amar; Mohamed Bouguessa; Abdoulaye Baniré Diallo (AAAI, 2023)

Adversarial Deep Embedded Clustering: On a better trade-off between Feature Randomness and Feature Drift (Extended abstract). - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (ICDE, 2023)

Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering (Extended abstract). - Nairouz Mrabah; Mohamed Bouguessa; Mohamed Fawzi Touati; Riadh Ksantini (ICDE, 2023)

Toward Convex Manifolds: A Geometric Perspective for Deep Graph Clustering of Single-cell RNA-seq Data. - Nairouz Mrabah; Mohamed Mahmoud Amar; Mohamed Bouguessa; Abdoulaye Baniré Diallo (IJCAI, 2023)

Beyond The Evidence Lower Bound: Dual Variational Graph Auto-Encoders For Node Clustering. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (SDM, 2023)

Rethinking Graph Auto-Encoder Models for Attributed Graph Clustering. - Nairouz Mrabah; Mohamed Bouguessa; Mohamed Fawzi Touati; Riadh Ksantini (IEEE Trans. Knowl. Data Eng., 2023)

A Geometric Perspective for High-Dimensional Multiplex Graphs. - Kamel Abdous; Nairouz Mrabah; Mohamed Bouguessa (CIKM, 2024)

A contrastive variational graph auto-encoder for node clustering. - Nairouz Mrabah; Mohamed Bouguessa; Riadh Ksantini (Pattern Recognit., 2024)

Hierarchical Aggregations for High-Dimensional Multiplex Graph Embedding. - Kamel Abdous; Nairouz Mrabah; Mohamed Bouguessa (IEEE Trans. Knowl. Data Eng., 2024)

Rethinking deep clustering paradigms: Self-supervision is all you need. - Amal Shaheen; Nairouz Mrabah; Riadh Ksantini; Abdulla Alqaddoumi (Neural Networks, 2025)

Sparsity Outperforms Low-Rank Projections in Few-Shot Adaptation. - Nairouz Mrabah; Nicolas Richet; Ismail Ben Ayed; Éric Granger (CoRR, 2025)

Low-Rank Expert Merging for Multi-Source Domain Adaptation in Person Re-Identification. - Taha Mustapha Nehdi; Nairouz Mrabah; Atif Belal; Marco Pedersoli; Eric Granger (CoRR, 2025)