• 
  Paul Saves, Jasper Bussemaker, Rémi Lafage, Thierry Lefebvre, Nathalie Bartoli, et al.. System-of-systems Modeling and Optimization: An Integrated Framework for Intermodal Mobility. ODAS 2024: 24th joint ONERA-DLR Aerospace Symposium, DLR, Jun 2024, Brunschweig, Germany. ⟨hal-04590323⟩
• 
  Renaud Ferrier, Mohamed Larbi Kadri, Sylvain Drapier, Pierre Gosselet. Apprentissage automatique d'EDPs contraintes par la physique pour l'identification des hétérogénéités dans les structures mécaniques élancées. 16è Colloque National en calcul des structures, CSMA, May 2024, Giens (Var), France. ⟨hal-04230541⟩
• 
  Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. Unsupervised learning of history-dependent constitutive material laws with thermodynamically-consistent neural networks in the modified Constitutive Relation Error framework.. Computer Methods in Applied Mechanics and Engineering, 2024, 425, pp.116967. ⟨10.1016/j.cma.2024.116967⟩. ⟨hal-04368755⟩
• 
  Héloïse Dandin, Adrien Leygue, Laurent Stainier. Graph-based representation of history-dependent material response in the Data-Driven Computational Mechanics framework. Computer Methods in Applied Mechanics and Engineering, 2024, 419, pp.116694. ⟨10.1016/j.cma.2023.116694⟩. ⟨hal-04259707v3⟩
• 
  Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. NN-mCRE: a modified Constitutive Relation Error framework for unsupervised learning of nonlinear state laws with physics-augmented Neural Networks. International Journal for Numerical Methods in Engineering, 2024, ⟨10.1002/nme.7439⟩. ⟨hal-04102108v2⟩
• 
  Paul Saves, Rémi Lafage, Nathalie Bartoli, Youssef Diouane, Jasper Bussemaker, et al.. SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes. Advances in Engineering Software, 2024, 188 (103571), pp.103571. ⟨10.1016/j.advengsoft.2023.103571⟩. ⟨hal-04331916⟩
• 
  Pramudita Satria Palar, Yohanes Bimo Dwianto, Lavi Rizki Zuhal, Joseph Morlier, Koji Shimoyama, et al.. Multi-objective design space exploration using explainable surrogate models. Structural and Multidisciplinary Optimization, 2024, 67 (38), ⟨10.1007/s00158-024-03769-z⟩. ⟨hal-04512428⟩
• 
  Paul Saves, Youssef Diouane, Nathalie Bartoli, Thierry Lefebvre, Joseph Morlier. High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft. Structural and Multidisciplinary Optimization, 2024, 67 (5), pp.81. ⟨10.1007/s00158-024-03785-z⟩. ⟨hal-04574274⟩
• 
  Rémy Charayron, Thierry Lefebvre, Nathalie Bartoli, Joseph Morlier. Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm. Aerospace Science and Technology, 2023, 142 (Part B), ⟨10.1016/j.ast.2023.108673⟩. ⟨hal-04254361⟩
• 
  Benoit Hilloulin, Abdelhamid Hafidi, Sonia Boudache, Ahmed Loukili. Interpretable ensemble machine learning for the prediction of the expansion of cementitious materials under external sulfate attack. Journal of Building Engineering, 2023, pp.107951. ⟨10.1016/j.jobe.2023.107951⟩. ⟨hal-04255480⟩
• 
  Edgar Zembra, Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. Use of physics-augmented neural networks for unsupervised learning of material constitutive relations - Comparison of the NN-Euclid and NN-mCRE methods. ENS Paris-Saclay; Centrale Supélec. 2023. ⟨hal-04255767⟩
• 
  Nathalie Bartoli, Thierry Lefebvre, Rémi Lafage, Paul Saves, Youssef Diouane, et al.. Multi-objective bayesian optimization with mixed-categorical design variables for expensive-to-evaluate aeronautical applications. AEROBEST 2023, ECCOMAS, Jul 2023, Lisbonne, Portugal. pp.436. ⟨hal-04170287⟩
• 
  Abdelhamid Hafidi, Benoit Hilloulin, Sonia Boudache, Umunnakwe Rejoice, Ahmed Loukili. Comparison of Machine Learning Algorithms for the Prediction of the External Sulphate Attack Resistance of Blended Cements. International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures. SynerCrete 2023., Jun 2023, Milos Island, Greece. pp.725-735, ⟨10.1007/978-3-031-33187-9_67⟩. ⟨hal-04131990⟩
• 
  Benoit Hilloulin, van Quan Tran. Interpretable machine learning model for autogenous shrinkage prediction of low-carbon cementitious materials. Construction and Building Materials, 2023, 396, pp.132343. ⟨10.1016/j.conbuildmat.2023.132343⟩. ⟨hal-04153200⟩
• 
  Paul Saves, Y. Diouane, Nathalie Bartoli, T. Lefebvre, J. Morlier. A mixed-categorical correlation kernel for Gaussian process. Neurocomputing, In press, ⟨10.1016/j.neucom.2023.126472⟩. ⟨hal-04130877v2⟩
• 
  Afsal Pulikkathodi, Elisabeth Longatte-Lacazedieu, Ludovic Chamoin, Juan-Pedro Berro Ramirez, Laurent Rota, et al.. A neural network-based data-driven local modeling of spotwelded plates under impact. Mechanics & Industry, 2023, 24, pp.34. ⟨10.1051/meca/2023029⟩. ⟨hal-04190457⟩
• 
  Raul Carreira Rufato, Youssef Diouane, Joël Henry, Richard Ahlfeld, Joseph Morlier. A mixed-categorical data-driven approach for prediction and optimization of hybrid discontinuous composites performance. AIAA AVIATION 2022 Forum, Jun 2022, Chicago, United States. pp.0, ⟨10.2514/6.2022-4037⟩. ⟨hal-03888070⟩
• 
  Paul Saves, Youssef Diouane, Nathalie Bartoli, Thierry Lefebvre, Joseph Morlier. A general square exponential kernel to handle mixed-categorical variables for Gaussian process. AIAA AVIATION 2022 Forum, Jun 2022, Chicago (virtual), France. ⟨10.2514/6.2022-3870⟩. ⟨hal-03700850⟩
• 
  Robin Grapin, Youssef Diouane, Joseph Morlier, Nathalie Bartoli, Thierry Lefebvre, et al.. Regularized Infill Criteria for Multi-objective Bayesian Optimization with Application to Aircraft Design. AIAA AVIATION 2022, Jun 2022, Chicago, United States. ⟨10.2514/6.2022-4053⟩. ⟨hal-03753674⟩
• 
  Benoit Hilloulin, Mathieu Lagrange, Marius Duvillard, Gauthier Garioud. ε-greedy automated indentation of cementitious materials for phase mechanical properties determination. Cement and Concrete Composites, 2022, 129, ⟨10.1016/j.cemconcomp.2022.104465⟩. ⟨hal-03596856v2⟩

• 
  Héloïse Dandin, Adrien Leygue, Laurent Stainier. Graph-based representation of history-dependent material response in the Data-Driven Computational Mechanics framework. Computer Methods in Applied Mechanics and Engineering, 2024, 419, pp.116694. ⟨10.1016/j.cma.2023.116694⟩. ⟨hal-04259707v3⟩
• 
  Paul Saves, Jasper Bussemaker, Rémi Lafage, Thierry Lefebvre, Nathalie Bartoli, et al.. System-of-systems Modeling and Optimization: An Integrated Framework for Intermodal Mobility. ODAS 2024: 24th joint ONERA-DLR Aerospace Symposium, DLR, Jun 2024, Brunschweig, Germany. ⟨hal-04590323⟩
• 
  Paul Saves, Youssef Diouane, Nathalie Bartoli, Thierry Lefebvre, Joseph Morlier. High-dimensional mixed-categorical Gaussian processes with application to multidisciplinary design optimization for a green aircraft. Structural and Multidisciplinary Optimization, 2024, 67 (5), pp.81. ⟨10.1007/s00158-024-03785-z⟩. ⟨hal-04574274⟩
• 
  Pramudita Satria Palar, Yohanes Bimo Dwianto, Lavi Rizki Zuhal, Joseph Morlier, Koji Shimoyama, et al.. Multi-objective design space exploration using explainable surrogate models. Structural and Multidisciplinary Optimization, 2024, 67 (38), ⟨10.1007/s00158-024-03769-z⟩. ⟨hal-04512428⟩
• 
  Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. Unsupervised learning of history-dependent constitutive material laws with thermodynamically-consistent neural networks in the modified Constitutive Relation Error framework.. Computer Methods in Applied Mechanics and Engineering, 2024, 425, pp.116967. ⟨10.1016/j.cma.2024.116967⟩. ⟨hal-04368755⟩
• 
  Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. NN-mCRE: a modified Constitutive Relation Error framework for unsupervised learning of nonlinear state laws with physics-augmented Neural Networks. International Journal for Numerical Methods in Engineering, 2024, ⟨10.1002/nme.7439⟩. ⟨hal-04102108v2⟩
• 
  Paul Saves, Rémi Lafage, Nathalie Bartoli, Youssef Diouane, Jasper Bussemaker, et al.. SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes. Advances in Engineering Software, 2024, 188 (103571), pp.103571. ⟨10.1016/j.advengsoft.2023.103571⟩. ⟨hal-04331916⟩
• 
  Edgar Zembra, Antoine Benady, Emmanuel Baranger, Ludovic Chamoin. Use of physics-augmented neural networks for unsupervised learning of material constitutive relations - Comparison of the NN-Euclid and NN-mCRE methods. ENS Paris-Saclay; Centrale Supélec. 2023. ⟨hal-04255767⟩
• 
  Benoit Hilloulin, Abdelhamid Hafidi, Sonia Boudache, Ahmed Loukili. Interpretable ensemble machine learning for the prediction of the expansion of cementitious materials under external sulfate attack. Journal of Building Engineering, 2023, pp.107951. ⟨10.1016/j.jobe.2023.107951⟩. ⟨hal-04255480⟩
• 
  Rémy Charayron, Thierry Lefebvre, Nathalie Bartoli, Joseph Morlier. Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm. Aerospace Science and Technology, 2023, 142 (Part B), ⟨10.1016/j.ast.2023.108673⟩. ⟨hal-04254361⟩
• 
  Renaud Ferrier, Mohamed Larbi Kadri, Sylvain Drapier, Pierre Gosselet. Apprentissage automatique d'EDPs contraintes par la physique pour l'identification des hétérogénéités dans les structures mécaniques élancées. 16è Colloque National en calcul des structures, CSMA, May 2024, Giens (Var), France. ⟨hal-04230541⟩
• 
  Afsal Pulikkathodi, Elisabeth Longatte-Lacazedieu, Ludovic Chamoin, Juan-Pedro Berro Ramirez, Laurent Rota, et al.. A neural network-based data-driven local modeling of spotwelded plates under impact. Mechanics & Industry, 2023, 24, pp.34. ⟨10.1051/meca/2023029⟩. ⟨hal-04190457⟩
• 
  Rémy Charayron, Thierry Lefebvre, Nathalie Bartoli, Joseph Morlier. Multi-fidelity constrained Bayesian optimization, application to drone design. Conference on Artificial Intelligence for Defense CAID, Direction Générale de l’Armement (DGA), Nov 2021, Rennes, France. ⟨hal-03891316v4⟩
• 
  Nathalie Bartoli, Thierry Lefebvre, Rémi Lafage, Paul Saves, Youssef Diouane, et al.. Multi-objective bayesian optimization with mixed-categorical design variables for expensive-to-evaluate aeronautical applications. AEROBEST 2023, ECCOMAS, Jul 2023, Lisbonne, Portugal. pp.436. ⟨hal-04170287⟩
• 
  Benoit Hilloulin, van Quan Tran. Interpretable machine learning model for autogenous shrinkage prediction of low-carbon cementitious materials. Construction and Building Materials, 2023, 396, pp.132343. ⟨10.1016/j.conbuildmat.2023.132343⟩. ⟨hal-04153200⟩
• 
  Paul Saves, Y. Diouane, Nathalie Bartoli, T. Lefebvre, J. Morlier. A mixed-categorical correlation kernel for Gaussian process. Neurocomputing, In press, ⟨10.1016/j.neucom.2023.126472⟩. ⟨hal-04130877v2⟩
• 
  Abdelhamid Hafidi, Benoit Hilloulin, Sonia Boudache, Umunnakwe Rejoice, Ahmed Loukili. Comparison of Machine Learning Algorithms for the Prediction of the External Sulphate Attack Resistance of Blended Cements. International RILEM Conference on Synergising Expertise towards Sustainability and Robustness of Cement-based Materials and Concrete Structures. SynerCrete 2023., Jun 2023, Milos Island, Greece. pp.725-735, ⟨10.1007/978-3-031-33187-9_67⟩. ⟨hal-04131990⟩
• 
  Raul Carreira Rufato, Youssef Diouane, Joël Henry, Richard Ahlfeld, Joseph Morlier. A mixed-categorical data-driven approach for prediction and optimization of hybrid discontinuous composites performance. AIAA AVIATION 2022 Forum, Jun 2022, Chicago, United States. pp.0, ⟨10.2514/6.2022-4037⟩. ⟨hal-03888070⟩
• 
  Benoit Hilloulin, Mathieu Lagrange, Marius Duvillard, Gauthier Garioud. ε-greedy automated indentation of cementitious materials for phase mechanical properties determination. Cement and Concrete Composites, 2022, 129, ⟨10.1016/j.cemconcomp.2022.104465⟩. ⟨hal-03596856v2⟩
• 
  Robin Grapin, Youssef Diouane, Joseph Morlier, Nathalie Bartoli, Thierry Lefebvre, et al.. Regularized Infill Criteria for Multi-objective Bayesian Optimization with Application to Aircraft Design. AIAA AVIATION 2022, Jun 2022, Chicago, United States. ⟨10.2514/6.2022-4053⟩. ⟨hal-03753674⟩

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