A Logical Approach to Extreme Opinion Diffusion. - Enzo Battistella; Laurence Cholvy (ICAART (2), 2018)

Modelling and Simulating Extreme Opinion Diffusion. - Enzo Battistella; Laurence Cholvy (ICAART (Revised Selected Papers), 2018)

Context Aware 3D CNNs for Brain Tumor Segmentation. - Siddhartha Chandra; Maria Vakalopoulou; Lucas Fidon; Enzo Battistella; Théo Estienne; Roger Sun; Charlotte Robert; Eric Deutsch; Nikos Paragios (BrainLes@MICCAI (2), 2018)

Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge. - Spyridon Bakas; Mauricio Reyes 001; András Jakab; Stefan Bauer; Markus Rempfler; Alessandro Crimi; Russell Takeshi Shinohara; Christoph Berger; Sung Min Ha; Martin Rozycki; Marcel Prastawa; Esther Alberts; et al. (CoRR, 2018)

Gene Expression High-Dimensional Clustering Towards a Novel, Robust, Clinically Relevant and Highly Compact Cancer Signature. - Enzo Battistella; Maria Vakalopoulou; Théo Estienne; Marvin Lerousseau; Roger Sun; Charlotte Robert; Nikos Paragios; Eric Deutsch (IWBBIO (1), 2019)

U-ReSNet: Ultimate Coupling of Registration and Segmentation with Deep Nets. - Théo Estienne; Maria Vakalopoulou; Stergios Christodoulidis; Enzo Battistella; Marvin Lerousseau; Alexandre Carre; Guillaume Klausner; Roger Sun; Charlotte Robert; Stavroula G. Mougiakakou; Nikos Paragios; Eric Deutsch (MICCAI (3), 2019)

Deep Learning Based Registration Using Spatial Gradients and Noisy Segmentation Labels. - Théo Estienne; Maria Vakalopoulou; Enzo Battistella; Alexandre Carré; Théophraste Henry; Marvin Lerousseau; Charlotte Robert; Nikos Paragios; Eric Deutsch (MICCAI (Challenges), 2020)

Weakly Supervised Multiple Instance Learning Histopathological Tumor Segmentation. - Marvin Lerousseau; Maria Vakalopoulou; Marion Classe; Julien Adam; Enzo Battistella; Alexandre Carré; Théo Estienne; Théophraste Henry; Eric Deutsch; Nikos Paragios (MICCAI (5), 2020)

AI-Driven CT-based quantification, staging and short-term outcome prediction of COVID-19 pneumonia. - Guillaume Chassagnon; Maria Vakalopoulou; Enzo Battistella; Stergios Christodoulidis; Trieu-Nghi Hoang-Thi; Severine Dangeard; Eric Deutsch; Fabrice André; Enora Guillo; Nara Halm; Stefany El Hajj; Florian Bompard; et al. (CoRR, 2020)

Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation. - Théo Estienne; Marvin Lerousseau; Maria Vakalopoulou; Emilie Alvarez Andres; Enzo Battistella; Alexandre Carré; Siddhartha Chandra; Stergios Christodoulidis; Mihir Sahasrabudhe; Roger Sun; Charlotte Robert; Hugues Talbot; et al. (Frontiers Comput. Neurosci., 2020)

Exploring Deep Registration Latent Spaces. - Théo Estienne; Maria Vakalopoulou; Stergios Christodoulidis; Enzo Battistella; Théophraste Henry; Marvin Lerousseau; Amaury Leroy; Guillaume Chassagnon; Marie-Pierre Revel; Nikos Paragios; Eric Deutsch (DART/FAIR@MICCAI, 2021)

Weakly Supervised Pan-Cancer Segmentation Tool. - Marvin Lerousseau; Marion Classe; Enzo Battistella; Théo Estienne; Théophraste Henry; Amaury Leroy; Roger Sun; Maria Vakalopoulou; Jean-Yves Scoazec; Eric Deutsch; Nikos Paragios (MICCAI (8), 2021)

Cancer Gene Profiling through Unsupervised Discovery. - Enzo Battistella; Maria Vakalopoulou; Roger Sun; Théo Estienne; Marvin Lerousseau; Sergey Nikolaev; Emilie Alvarez Andres; Alexandre Carré; Stéphane Niyoteka; Charlotte Robert; Nikos Paragios; Eric Deutsch (CoRR, 2021)

MICS : Multi-steps, Inverse Consistency and Symmetric deep learning registration network. - Théo Estienne; Maria Vakalopoulou; Enzo Battistella; Théophraste Henry; Marvin Lerousseau; Amaury Leroy; Nikos Paragios; Eric Deutsch (CoRR, 2021)

AI-driven quantification, staging and outcome prediction of COVID-19 pneumonia. - Guillaume Chassagnon; Maria Vakalopoulou; Enzo Battistella; Stergios Christodoulidis; Trieu-Nghi Hoang-Thi; Severine Dangeard; Eric Deutsch; Fabrice André; Enora Guillo; Nara Halm; Stefany El Hajj; Florian Bompard; et al. (Medical Image Anal., 2021)

High Dimensional Graph Theoretical Approaches for Various Omics Data. (Approches de théorie des graphes d'ordre supérieur pour diverses données omiques). - Enzo Battistella (2021)

COMBING: Clustering in Oncology for Mathematical and Biological Identification of Novel Gene Signatures. - Enzo Battistella; Maria Vakalopoulou; Roger Sun; Théo Estienne; Marvin Lerousseau; Sergey Nikolaev; Emilie Alvarez Andres; Alexandre Carré; Stéphane Niyoteka; Charlotte Robert; Nikos Paragios; Eric Deutsch (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

GHOST: Graph-based higher-order similarity transformation for classification. - Enzo Battistella; Maria Vakalopoulou; Nikos Paragios; Eric Deutsch (Pattern Recognit., 2024)

ralphi: A Deep Reinforcement Learning Framework for Haplotype Assembly. - Enzo Battistella; Anant Maheshwari; Baris Ekim; Bonnie Berger; Victoria Popic (RECOMB, 2025)

Understanding high-order network structure using permissible walks on attributed hypergraphs. - Audun Myers; Enzo Battistella; Sean English; Robert Green; Cliff A. Joslyn; Evgeniya Lagoda; Van Magnan; Evan D. Nash; Michael Robinson 001 (J. Complex Networks, 2025)