Publications 1991-2026

• 2026
  • H. Salman, J.‑F. Pradat‑Peyre, S. Guehis, N. Chrara, Ch. Zaki, A. Nasser : “A New Communication Efficient Federated Online Distillation for Non-IID Data: Application to Fetal Brain Ultrasound Plane Classification”, Neuroscience Informatics, vol. 6 (2), pp. 100272, (Elsevier) (2026)
  • H. Salman, J.‑F. Pradat‑Peyre, S. Guehis, N. Charara, Ch. Zaki, A. Nasser : “FedAK: a semi-supervised one-shot framework for heterogeneous federated learning via feature-level attention-based knowledge distillation”, Scientific Reports, pp. salman2026, (Nature Publishing Group) (2026)
  • Th. Anani, J.‑F. Pradat‑Peyre, F. Delbot, C. Desnuelle, A.‑S. Rolland, D. Devos, P.‑F. Pradat : “Feature selection using metaheuristics to predict annual amyotrophic lateral sclerosis progression.”, Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, vol. 27 (1-2), pp. 62-77, (Taylor & Francis) (2026)
• 2025
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Toward Robust Prediction : An Empirical Study of Feature Selection Methods”, (2025)
  • H. Salman, Ch. Zaki, N. Charara, S. Guehis, J.‑F. Pradat‑Peyre, A. Nasser : “Knowledge distillation in federated learning: a comprehensive survey”, Discover Computing, vol. 28 (1), pp. 145, (Springer) (2025)
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Comparaison expérimentale d’algorithmes d’invalidation automatique de conjectures en théorie des graphes”, (2025)
• 2024
  • Th. Anani, J.‑F. Pradat‑Peyre, F. Delbot, P.‑F. Pradat : “Machine Learning and Feature Selection Methods to Predict 1-Year Disease Progression for Amyotrophic Lateral Sclerosis”, (2024)
• 2022
  • Th. Anani, J.‑F. Pradat‑Peyre, F. Delbot, P.‑F. Pradat : “Use of metaheuristics for machine learning in the context of ALS”, 8^th ALS and MND research meeting, Paris, France (2022)
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Experimental Comparison of Metaheuristics for Feature Selection in Machine Learning in the Medical Context”, Artificial Intelligence Applications and Innovations, vol. AICT-647 (Part II), IFIP Advances in Information and Communication Technology, Hersonissos, Greece, pp. 194-205, (Springer International Publishing), (ISBN: 978-3-031-08336-5) (2022)
  • Th. Anani, F. Delbot, J.‑F. Pradat‑Peyre : “Comparaison expérimentale de métaheuristiques pour la sélection de variables dans le cadre de l’apprentissage automatique appliqué au domaine médical”, 23^e congrès annuel de la Société Française de Recherche Opérationnelle et d'Aide à la Décision, Villeurbanne - Lyon, France (2022)
• 2021
  • V. Grollemund, G. Le Chat, M.‑S. Secchi‑Buhour, F. Delbot, J.‑F. Pradat‑Peyre, P. Bede, P.‑F. Pradat : “Manifold learning for amyotrophic lateral sclerosis functional loss assessment”, Journal of Neurology, vol. 268 (3), pp. 825-850, (Springer Verlag) (2021)
  • J.‑F. Pradat‑Peyre, J. Printz : “Pratique des tests logiciels - 4^e édition: Améliorer la qualité par les tests. Gérer une campagne de tests. Préparer la certification ISTQB, EAN 9782100819959”, InfoPro, (Dunod), (ISBN: 9782100819959) (2021)
• 2020
  • V. Grollemund, G. Chat, M.‑S. Secchi‑Buhour, F. Delbot, J.‑F. Pradat‑Peyre, P. Bede, P.‑F. Pradat : “Development and validation of a 1-year survival prognosis estimation model for Amyotrophic Lateral Sclerosis using manifold learning algorithm UMAP”, Scientific Reports, vol. 10 (1), pp. 13378, (Nature Publishing Group) (2020)
  • V. Grollemund, G. Chat, J.‑F. Pradat‑Peyre, F. Delbot : “Manifold Learning for Innovation Funding: Identification of Potential Funding Recipients”, Artificial Intelligence Applications and Innovations, vol. 583, IFIP Advances in Information and Communication Technology, Neos Marmaras, Greece, pp. 119-127, (Springer International Publishing) (2020)
• 2019
  • V. Bouquet, K. Christophe, F. Delbot, G. Chat, J.‑F. Pradat‑Peyre : “Minimum Dominating Set and Maximum Independent Set for Evaluation of EU Funding Polices in Collaboration Networks”, Operations Research Proceedings 2018, Operations Research Proceedings, Brussels, Belgium, pp. 243-249, (Springer International Publishing) (2019)
  • V. Grollemund, P.‑F. Pradat, G. Querin, F. Delbot, G. Le Chat, J.‑F. Pradat‑Peyre, P. Bede : “Machine Learning in Amyotrophic Lateral Sclerosis: Achievements, Pitfalls, and Future Directions”, Frontiers in Neuroscience, vol. 13, pp. 135, (Frontiers) (2019)
• 2018
  • S. Zairi, B. Zouari, H. Rahal, J.‑F. Pradat‑Peyre : “A generic generalized stochastic Petri nets model for the performance analysis of FMS considering the resources failures”, 2018 5^th International Conference on Control, Decision and Information Technologies (CoDIT), Thessaloniki, Greece, pp. 737-742, (IEEE) (2018)
• 2011
  • J.‑F. Pradat‑Peyre, Y. Thierry‑Mieg : “Verification of Finite-State Systems”, chapter in Models and Analysis in Distributed Systems, pp. 155-220, (Wiley), (ISBN: 9781848213142) (2011)
• 2009
  • S. Haddad, F. Kordon, L. Petrucci, J.‑F. Pradat‑Peyre, N. Trèves : “Efficient State-Based Analysis by Introducing Bags in Petri Nets Color Domains”, Proceedings of the 28^th American Control Conference (ACC'09), Saint Louis, MO, United States, pp. 5018-5025, (IEEE) (2009)
  • C. KAISER, J.‑F. Pradat‑Peyre : “Weak Fairness Semantic Drawbacks in Java Multithreading”, Reliable Software Technologies – Ada-Europe 2009, vol. 5570, Lecture Notes in Computer Science, Brest, France, pp. 90-104, (Springer Berlin Heidelberg) (2009)
  • C. Girault, J.‑F. Pradat‑Peyre : “Analysis of High Level Petri Nets”, chapter in Petri Nets: Fundamental Models, Verification and Applications, pp. 221-266, (Wiley-ISTE), (ISBN: 9781848210790) (2009)
  • C. Girault, J.‑F. Pradat‑Peyre : “High Level Petri Nets”, chapter in Petri Nets: Fundamental Models, Verification and Applications, pp. 185-219, (Wiley-ISTE), (ISBN: 9781848210790) (2009)
  • J.‑F. Pradat‑Peyre, J. Printz : “Pratique des tests logiciels Concevoir et mettre en oeuvre une stratégie de tests. Préparation à la certification ISTQB”, InfoPro, (Dunod), (ISBN: 9782100518623) (2009)
• 2008
  • Ch. Pajault, J.‑F. Pradat‑Peyre, P. Rousseau : “Adapting Petri Nets Reductions to Promela Specifications”, Formal Techniques for Networked and Distributed Systems - FORTE 2008, 28^th IFIP WG 6.1 International Conference, vol. 5048, Lecture Notes in Computer Science, Tokyo, Japan, pp. 84-98, (Springer-Verlag) (2008)
  • C. KAISER, Ch. Pajault, J.‑F. Pradat‑Peyre : “Concurrent Program Metrics Drawn by Quasar”, Ada-Europe 2008, 13^th Ada-Europe International Conference on Reliable Software Technologies, vol. 5026, Lecture Notes in Computer Science, Venice, Italy, pp. 101-114, (Springer-Verlag) (2008)
• 2001
  • C. Girault, J.‑F. Pradat‑Peyre : “Les Réseaux de Petri de Haut Niveau”, chapitre de Les Réseaux de Petri, Modèles Fondamentaux, pp. 223-254, (Hermes), (ISBN: 2-7462-0250-6) (2001)
• 2000
  • D. Poitrenaud, J.‑F. Pradat‑Peyre : “Pre and post-agglomerations for LTL model checking”, 21^th International Conference on Applications and Theory of Petri Nets, vol. 1825, Lecture Notes in Computer Science, Aarhus, Denmark, pp. 387-408, (Springer) (2000)
• 1991
  • F. Kordon, J.‑F. Pradat‑Peyre : “Process decomposition for Rapid Prototyping of Parallel systems”, 6^th International Symposium on Computer and Information Science, Antalya, Türkiye (1991)