Patrice Aknin
Publications
Publications
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Training as an affordable and powerful lever to stimulate the evolution dynamics of a newly designed technology platform at the frontier between academia and industry25th International Conference on Engineering Design (ICED), Aug 2025, Dallas, United States. ⟨10.1017/pds.2025.10337⟩ |
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Strengthening the generative power of a scientific and industrial ecosystem: the case of the SystemX Institute for Technological Research (IRT), a "double impact Research and Technology Organization (RTO)"?EURAM - European Academy of Management, Jun 2022, Zurich, Switzerland |
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Modèle LSTM encodeur-prédicteur pour la prévision court-terme de l'affluence dans les transports collectifsCAP 2019, Conférence sur l'Apprentissage Automatique, Jul 2019, Toulouse, France |
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Apprentissage automatique sur des données de type graphe utilisant le plongement de Poincaré et les algorithmes stochastiques riemanniensConférence Nationale d'Intelligence Artificielle Année 2019, Jul 2019, Toulouse, France |
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DESIGNING THE MISSING LINK BETWEEN SCIENCE AND INDUSTRY: ORGANIZING PARTNERSHIP BASED ON DUAL GENERATIVITYInternational Conference on Engineering Design, 2017, Vancouver, Canada |
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Dynamic bayesian networks for reliability analysis: from a Markovian point of view to semi-markovian approachesSAFEPROCESS'15 - 9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes, Sep 2015, PARIS, France. pp. 694-700, ⟨10.1016/j.ifacol.2015.09.608⟩ |
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A specific semi-markovian dynamic bayesian network estimating residual useful life16th ASMDA Conference, Jun 2015, LE PIREE, Greece. 13 p |
A specific Dynamic Bayesian Network for a prognosis based maintenance strategyThe Second International Conference on Railway Technology: Research, Development and Maintenance, Apr 2014, Ajaccio, France. 18p |
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Spatio-temporal Analysis of Dynamic Origin-Destination Data Using Latent Dirichlet Allocation: Application to Vélib' Bike Sharing System of ParisTRB 93rd Annual meeting, Jan 2014, France. 19p |
How to keep optimal maintenance strategies with a dynamic optimization approach?The Second International Conference on Railway Technology: Research, Development and Maintenance, Apr 2014, France. 12p |
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Hierarchical and multiscale Mean Shift segmentation of population grid22th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2013), Apr 2013, Bruges, Belgium |
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A mixture of Kalman filters for online monitoring of railway switches12th International Conference on Railway Engineering, Jul 2013, london, United Kingdom. 9p |
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Floating Train Data Systems for Preventive Maintenance: A Data Mining ApproachInternational Conference on Industrial Engineering and Systems Management (IESM 2013), Oct 2013, Morocco. 7p |
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Hierarchical and multiscale Mean Shift segmentation of population grid22th European Symposium on Artificial Neural Networks (ESANN 2013), Apr 2013, Belgium. 6p |
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Un modèle dynamique à variables latentes pour le partitionnement de données temporelles45e Journées de Statistique (JdS 2013), May 2013, Toulouse, France. pp.1-6 |
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Mining floating train data sequences for temporal association rules within a predictive maintenance frameworkIEEE Industrial Conference on Data Mining (ICDM 2013), Dec 2013, France. 15p |
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State-space modeling of a sequence of curves application to the condition condition monitoring of railway switches23rd IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2013), Sep 2013, France. 6p |
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Model-Based Clustering of Temporal Data23rd International Conference on Artificial Neural Networks (ICANN 2013), Sep 2013, Sofia, Bulgaria. pp.9-16 |
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A rollingstock door system’s dynamic maintenance strategies based on a sensitivity analysis through bayesian networks10th World Congress on Railway Research (WCRR 2013), Nov 2013, Sydney, Australia. 8p |
A Probabilistic Graphical Models approach for rail prognosis based maintenance in a periodic observations contextInternational Conference on Railway Engineering, Jun 2013, Beijing, China. 14p |
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A prognostic algorithm based on probabilistic graphical models for a periodically observable systemEuropean Safety and Reliability Conference (ESREL 2013), Sep 2013, Amsterdam, Netherlands. 8p |
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Online predictive diagnosis of electrical train door systems10th World Congress on Railway Research (WCRR 2013), Nov 2013, Sydney, Australia. 6p |
A Dynamic clustering approach for tracking the evolution of railway componentsInternational Conference on Condition Monitoring (CM 2013), Jun 2013, Poland. 9p |
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A Sequential Testing Procedure for Multiple Change-Point Detection in a Stream of Pneumatic Door SignaturesThe 12th IEEE International Conference on Machine Learning and Applications, Dec 2013, France. 6p |
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Segmentation multi-échelle de grilles régulières de population pour l'identification des formes urbaines35ème journée ISS France, Feb 2012, Paris, France |
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Classification automatique de données temporelles en classes ordonnées44e Journées de Statistique, SFdS, May 2012, Bruxelles, Belgique. pp.1-6 |
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Optimal preventive maintenance schedules using specific genetic algorithms and probabilistic graphical modelProc. of the ESREL’2011 Conference. Advances in Safety, Reliability and Risk Management, 2012, London, United Kingdom. pp.901-909 |
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A pattern recognition approach for anomaly detection on buses brake system14th International IEEE Conference on Intelligent Transportation Systems, Oct 2011, France. pp 266-271 |
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Identification de formes urbaines à partir de grilles régulières de populationColloque Images et Villes, Dec 2011, Paris, France |
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VirMaLab - A generic approach for optimizing maintenance policies of complex systemsWCRR 2011 - 9th World Congress on Railway Research, May 2011, LILLE, France. 11p |
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Classification automatique de données temporelles en classes ordonnées43èmes Journées de Statistique, SFdS, May 2011, Gammarth, Tunisie. pp.1-6 |
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Optimal preventive maintenance schedules using specific genetic algorithms and probabilistic graphical model9th European Safety and Reliability International Conference, ESREL'11, Sep 2011, France. 8p |
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Model-based clustering with Hidden Markov Model regression for time series with regime changes2011 International Joint Conference on Neural Networks, Jul 2011, San Jose, California, United States. pp.2814-2821 |
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A dynamic probabilistic modeling of railway switches operating statesWCRR 2011 - 9th World Congress on Railway Research, May 2011, LILLE, France. 6p |
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Optimisation par algorithme génétique de la maintenance préventive dans un contexte de modélisation par réseaux bayésiens dynamiques17ème Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, 2010, La Rochelle, France |
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Semi-supervised feature extraction using independent factor analysisICOR, 9th International Conference on Operations Research, Feb 2010, La Havanne, Cuba. 8p |
VirMaLab - Une approche générique pour modéliser la maintenance de systèmes complexes17ème Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, Lambda Mu 2010, Oct 2010, France. 8p |
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Optimisation par algorithme génétique de la maintenance préventive dans un contexte de modélisation par modèles graphiques probabilistesLambda Mu 17, 17ème Congrès de Maîtrise des Risques et de Sûreté de Fonctionnement, Oct 2010, La Rochelle, France. 10p |
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A regression model with a hidden logistic process for signal parametrization17th European Symposium on Artificial Neural Networks, Advances in Computational Intelligence and Learning, Apr 2009, Bruges, Belgium. pp.1-6 |
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A regression model with a hidden logistic process for feature extraction from time serieIJCNN'09 International Joint Conference on Neural Networks, Jun 2009, Atlanta, United States. pp.1-8 |
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Partially-supervised learning in Independent Factor AnalysisEuropean Symposium on Artificial Neural Networks (ESANN), Apr 2009, Bruges, Belgium. pp.53--58 |
Analyse en composantes indépendantes parcimonieuse pour le diagnostic de systèmes répartisXXe colloque GRETSI, 2009, Dijon, France |
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Noiseless Independent Factor Analysis with Mixing Constraints in a Semi-supervised Framework. Application to Railway Device Fault DiagnosisInternational Conference on Artificial Neural Network, Sep 2009, Limassol, Cyprus. pp.416-425 |
Specific graphical models for analyzing the reliabilityMED'08, 2008, Ajaccio, France. pp.621-626 |
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Dynamic bayesian networks modelling maintenance strategies: Prevention of broken rails8th World Congress on Railway Research (WCRR 2008), May 2008, Seoul, South Korea |
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Mixture model estimation with soft labelsFourth International Workshop on Soft Methods in Probabilities and Statistics, Sep 2008, Toulouse, France. pp.165-174 |
Approches markovienne et semi-markovienne pour la modélisation de la fiabilité et des actions de maintenance d'un système ferroviaireWorkshop Surveillance, Sûreté et Sécurité des Grands Systèmes (3SGS'08), 2008, Troyes, France |
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Reliability analysis using graphical duration modelsARES 2008, 2008, Barcelona, Spain. pp.795-800 |
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Approche semi-markovienne pour la modélisation de stratégies de maintenance: application à la prévention de rupture du railMOSIM'2008, 2008, Paris, France. pp.CDROM |
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Réseaux bayésiens dynamiques pour la représentation de modèles de durée en temps discretJournées Francophone sur les Réseaux Bayésiens, May 2008, Lyon, France |
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A Subspace Method for Detection and Classification of Rail Defects16th European Signal Processing Conference, EUSIPCO-2008, Aug 2008, Lausanne, Switzerland. pp.CDROM |
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Semi-supervised IFA with prior knowledge on the mixing process. An application to a railway device diagnosis.International Conference on Machine Learning and Application, Dec 2008, san-diego, United States. pp.415 - 420 |
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Noiseless Independent Factor Analysis with mixing constraints in a semi-supervised framework. Application to railway device fault diagnosis.International Conference on Artificial Neural Networks (ICANN),, Sep 2009, Limassol, Cyprus. pp.416-425, ⟨10.1007/978-3-642-04277-5_42⟩ |
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A generic approach to model complex system reliability using graphical duration modelsMathematical Methods in Reliability: Methodology and Practice (MMR 2007),, 2007, Glasgow, United Kingdom |
Railway infrastructure system diagnosis using Empirical Mode Decomposition and Hilbert transformIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2006, Toulouse, France. pp.III, ⟨10.1109/ICASSP.2006.1660866⟩ |
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Recherche à visée sociétale, un enjeu pour nous tousSéminaire Inrets, Mar 2004, Autrans, France |
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Ho–Kashyap with Early Stopping Versus Soft Margin SVM for Linear Classifiers –An ApplicationInternational Symposium on Neural Networks, Aug 2004, Dalian, China. pp.524-530, ⟨10.1007/b99834⟩ |
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A dynamic graphical model to represent complex survival distributionsAdvances in Mathematical Modeling for Reliability, IOS Press, pp.17-24, 2008 |