On the expansion of "dangerous" gene families in vertebrates. - Séverine Affeldt; Param Priya Singh; Giulia Malaguti; Hervé Isambert (BMC Bioinform., 2014)

Human Dominant Disease Genes Are Enriched in Paralogs Originating from Whole Genome Duplication. - Param Priya Singh; Séverine Affeldt; Giulia Malaguti; Hervé Isambert (PLoS Comput. Biol., 2014)

Robust Reconstruction of Causal Graphical Models based on Conditional 2-point and 3-point Information. - Séverine Affeldt; Hervé Isambert (ACI@UAI, 2015)

Network reconstruction and causal analysis in systems biology. (Reconstruction de réseaux fonctionnels et analyse causale en biologie des systèmes). - Séverine Affeldt (2015)

Spectral consensus strategy for accurate reconstruction of large biological networks. - Séverine Affeldt; Nataliya Sokolovska; Edi Prifti; Jean-Daniel Zucker (BMC Bioinform., 2016)

3off2: A network reconstruction algorithm based on 2-point and 3-point information statistics. - Séverine Affeldt; Louis Verny; Hervé Isambert (BMC Bioinform., 2016)

Efficient global network learning from local reconstructions. - Séverine Affeldt; Nataliya Sokolovska; Edi Prifti; Jean-Daniel Zucker (IJCNN, 2017)

Learning causal networks with latent variables from multivariate information in genomic data. - Louis Verny; Nadir Sella; Séverine Affeldt; Param Priya Singh; Hervé Isambert (PLoS Comput. Biol., 2017)

MIIC online: a web server to reconstruct causal or non-causal networks from non-perturbative data. - Nadir Sella; Louis Verny; Guido Uguzzoni; Séverine Affeldt; Hervé Isambert (Bioinform., 2018)

Ensemble Block Co-clustering: A Unified Framework for Text Data. - Séverine Affeldt; Lazhar Labiod; Mohamed Nadif (CIKM, 2020)

Spectral clustering via ensemble deep autoencoder learning (SC-EDAE). - Séverine Affeldt; Lazhar Labiod; Mohamed Nadif (Pattern Recognit., 2020)

Approche ensemble pour le co-clustering par blocs sur des données textuelles: Application au biomédical. - Séverine Affeldt; Lazhar Labiod; Mohamed Nadif (EGC, 2021)

Méthode ensemble de clustering profond. - Séverine Affeldt; Lazhar Labiod; Mohamed Nadif (EGC, 2021)

Regularized Dual-PPMI Co-clustering for Text Data. - Séverine Affeldt; Lazhar Labiod; Mohamed Nadif (SIGIR, 2021)

Regularized bi-directional co-clustering. - Séverine Affeldt; Lazhar Labiod; Mohamed Nadif (Stat. Comput., 2021)

Apprentissage machine pour la prédiction de l'attrition: une étude comparative. - Louis Geiler; Séverine Affeldt; Mohamed Nadif (EGC, 2022)

An effective strategy for churn prediction and customer profiling. - Louis Geiler; Séverine Affeldt; Mohamed Nadif (Data Knowl. Eng., 2022)

A survey on machine learning methods for churn prediction. - Louis Geiler; Séverine Affeldt; Mohamed Nadif (Int. J. Data Sci. Anal., 2022)

CAEclust: A Consensus of Autoencoders Representations for Clustering. - Séverine Affeldt; Lazhar Labiod; Mohamed Nadif (Image Process. Line, 2022)

CORPEX : Analyse exploratoire d'un corpus biomédical à l'aide de la classification croisée. - Amine Ferdjaoui; Amira Tlati; Séverine Affeldt; Mohamed Nadif (EGC, 2023)

Attentive Perturbation: Extending Prefix Tuning to Large Language Models Inner Representations. - Louis Falissard; Séverine Affeldt; Mohamed Nadif (LOD (1), 2023)

Modèles graphiques causaux interactifs pour les données textuelles. - Amine Ferdjaoui; Séverine Affeldt; Mohamed Nadif (EGC, 2024)

WordGraph: A Python Package for Reconstructing Interactive Causal Graphical Models from Text Data. - Amine Ferdjaoui; Séverine Affeldt; Mohamed Nadif (WSDM, 2024)

Cluster Insight: A Weighted Clustering Tool for Large Textual Data Exploration. - Amine Ferdjaoui; Séverine Affeldt; Mohamed Nadif (WSDM, 2025)