papers

Publications (7)

cs.LG2022

dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification

Paul Boniol, Mohammed Meftah, Emmanuel Remy +1

Data series classification is an important and challenging problem in data science. Explaining the classification decisions by finding the discriminant parts of the input that led…

stat.ME2016

Stochastic simulators based optimization by Gaussian process metamodels -- Application to maintenance investments planning issues

Thomas Browne, Bertrand Iooss, Loïc Le Gratiet +2

This paper deals with the optimization of industrial asset management strategies, whose profitability is characterized by the Net Present Value (NPV) indicator which is assessed by…

stat.CO2026

Digital twin-based hybrid framework for steam generator clogging prognostics

Edgar Jaber, Emmanuel Remy, Vincent Chabridon +5

We present a hybrid framework to support prognostics of the clogging degradation phenomenon in tube support plates for digital twins of steam generators in pressurized water reacto…

stat.ME2025

Fusion of heterogeneous data for robust degradation prognostics

Edgar Jaber, Emmanuel Remy, Vincent Chabridon +2

Assessing the degradation state of an industrial asset first requires evaluating its current condition and then to project the forecast model trajectory to a predefined prognostic…

stat.CO2024

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…

stat.ML2024

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…

stat.AP2014

On the practical interest of discrete Inverse Polya and Weibull-1 models in industrial reliability studies

Alberto Pasanisi, Côme Roero, Nicolas Bousquet +1

Engineers often cope with the problem of assessing the lifetime of industrial components, under the basis of observed industrial feedback data. Usually, lifetime is modelled as a c…