Publications (36)
Sensitivity Analyses of a Multi-Physics Long-Term Clogging Model For Steam Generators
Edgar Jaber, Vincent Chabridon, Emmanuel Remy +4
Long-term operation of nuclear steam generators can result in the occurrence of clogging, a deposition phenomenon that may increase the risk of mechanical and vibration loadings on…
Conformal Approach To Gaussian Process Surrogate Evaluation With Coverage Guarantees
Edgar Jaber, Vincent Blot, Nicolas Brunel +6
Gaussian processes (GPs) are a Bayesian machine learning approach widely used to construct surrogate models for the uncertainty quantification of computer simulation codes in indus…
Fixed-budget online adaptive learning for physics-informed neural networks. Towards parameterized problem inference
Thi Nguyen Khoa Nguyen, Thibault Dairay, Raphaël Meunier +2
Physics-Informed Neural Networks (PINNs) have gained much attention in various fields of engineering thanks to their capability of incorporating physical laws into the models. PINN…
Functional approach for excess mass estimation in the density model
Cristina Butucea, Mathilde Mougeot, Karine Tribouley
We consider a multivariate density model where we estimate the excess mass of the unknown probability density at a given level from i.i.d. observed random variables.…
Geometry-aware framework for deep energy method: an application to structural mechanics with hyperelastic materials
Thi Nguyen Khoa Nguyen, Thibault Dairay, Raphaël Meunier +2
Physics-Informed Neural Networks (PINNs) have gained considerable interest in diverse engineering domains thanks to their capacity to integrate physical laws into deep learning mod…
Multi-Component VAE with Gaussian Markov Random Field
Fouad Oubari, Mohamed El-Baha, Raphael Meunier +2
Multi-component datasets with intricate dependencies, like industrial assemblies or multi-modal imaging, challenge current generative modeling techniques. Existing Multi-component…