Predictive Classification of Water Consumption Time Series Using Non-homogeneous Markov Models. - Milad Leyli-Abadi; Allou Samé; Latifa Oukhellou; Nicolas Cheifetz; Pierre Mandel; Cédric Féliers; Olivier Chesneau (DSAA, 2017)

Denoising Autoencoder as an Effective Dimensionality Reduction and Clustering of Text Data. - Milad Leyli-Abadi; Lazhar Labiod; Mohamed Nadif (PAKDD (2), 2017)

Mixture of Non-homogeneous Hidden Markov Models for Clustering and Prediction of Water Consumption Time Series. - Milad Leyli-Abadi; Allou Samé; Latifa Oukhellou; Nicolas Cheifetz; Pierre Mandel; Cédric Féliers; Olivier Chesneau (IJCNN, 2018)

Change Point Detection in Periodic Panel Data Using a Mixture-Model-Based Approach. - Allou Samé; Milad Leyli-Abadi (PAKDD (Workshops), 2019)

Mixture of Joint Nonhomogeneous Markov Chains to Cluster and Model Water Consumption Behavior Sequences. - Milad Leyli-Abadi; Allou Samé; Latifa Oukhellou; Nicolas Cheifetz; Pierre Mandel; Cédric Féliers; Olivier Chesneau (ACM Trans. Intell. Syst. Technol., 2019)

Modélisation dynamique, classification et détection de changement dans les panels catégoriels issus d'un réseau d'eau intelligent. (Dynamic modelling, clustering and change detection in categorical panel data issued from smart water grids). - Milad Leyli-Abadi (2019)

Road Patterns Identification and Risk Analysis Based on Machine Learning Framework: Powered Two-Wheelers Case. - Milad Leyli-Abadi; Abderrahmane Boubezoul; Stéphane Espié (IDEAL (2), 2020)

Non-Supervised Trajectory Segmentation and Cross Analysis of Riders' Dynamic Behavior in a Simulated Riding Platform. - Milad Leyli-Abadi; Abderrahmane Boubezoul; Stéphane Espié (ISC2, 2020)

Riding Pattern Recognition for Powered Two-Wheelers Using a Long Short-Term Memory Network. - Milad Leyli-Abadi; Abderrahmane Boubezoul; Latifa Oukhellou (ITSC, 2020)

Deep Neural Networks for Classification of Riding Patterns: with a focus on explainability. - Milad Leyli-Abadi; Abderrahmane Boubezoul (ESANN, 2021)

Online common change-point detection in a set of nonstationary categorical time series. - Milad Leyli-Abadi; Allou Samé; Latifa Oukhellou; Nicolas Cheifetz; Pierre Mandel; Cédric Féliers; Véronique Heim (Neurocomputing, 2021)

Benchmarking and deeper analysis of adversarial patch attack on object detectors. - Pol Labarbarie; Adrien Chan-Hon-Tong; Stéphane Herbin; Milad Leyli-Abadi (AISafety@IJCAI, 2022)

LIPS - Learning Industrial Physical Simulation benchmark suite. - Milad Leyli-Abadi; Antoine Marot; Jérôme Picault; David Danan; Mouadh Yagoubi; Benjamin Donnot; Seif Attoui; Pavel Dimitrov; Asma Farjallah; Clement Etienam (NeurIPS, 2022)

Carpet-bombing patch: attacking a deep network without usual requirements. - Pol Labarbarie; Adrien Chan-Hon-Tong; Stéphane Herbin; Milad Leyli-Abadi (CoRR, 2022)

Evaluation methodology for disentangled uncertainty quantification on regression models. - Kevin Pasini; Clément Arlotti; Milad Leyli-Abadi; Marc Nabhan; Johanna Baro (ESANN, 2024)

Optimal transport based adversarial patch to leverage large scale attack transferability. - Pol Labarbarie; Adrien Chan-Hon-Tong; Stéphane Herbin; Milad Leyli-Abadi (ICLR, 2024)

ML4PhySim : Machine Learning for Physical Simulations Challenge (The airfoil design). - Mouadh Yagoubi; Milad Leyli-Abadi; David Danan; Jean-Patrick Brunet; Jocelyn Ahmed Mazari; Florent Bonnet; Asma Farjallah; Marc Schoenauer; Patrick Gallinari (CoRR, 2024)

NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design. - Mouadh Yagoubi; David Danan; Milad Leyli-Abadi; Jean-Patrick Brunet; Jocelyn Ahmed Mazari; Florent Bonnet; Maroua Gmati; Asma Farjallah; Paola Cinnella; Patrick Gallinari; Marc Schoenauer (CoRR, 2024)

A Conceptual Framework for AI-based Decision Systems in Critical Infrastructures. - Milad Leyli-Abadi; Ricardo J. Bessa; Jan Viebahn; Daniel Boos; Clark Borst; Alberto Castagna; Ricardo Chavarriaga; Mohamed Hassouna; Bruno Lemetayer; Giulia Leto; Antoine Marot; Maroua Meddeb; et al. (CoRR, 2025)

Statistical and Predictive Analysis to Identify Risk Factors and Effects of Post COVID-19 Syndrome. - Milad Leyli-Abadi; Jean-Patrick Brunet; Axel Tahmasebimoradi (CoRR, 2025)

Machine Learning for Physical Simulation Challenge Results and Retrospective Analysis: Power Grid Use Case. - Milad Leyli-Abadi; Jérôme Picault; Antoine Marot; Jean-Patrick Brunet; Agathe Gilain; Amarsagar Reddy Ramapuram Matavalam; Shaban Ghias Satti; Qingbin Jiang; Yang Liu; Dean Justin Ninalga (CoRR, 2025)

NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis. - Mouadh Yagoubi; David Danan; Milad Leyli-Abadi; Jocelyn Ahmed Mazari; Jean-Patrick Brunet; Abbas Kabalan; Fabien Casenave; Yuxin Ma; Giovanni Catalani; Jean Fesquet; Jacob Helwig; Xuan Zhang; et al. (CoRR, 2025)