Benoît Celse
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View article: Heterogeneous transfer learning for highly non-linear regression tasks with application to the hydrotreatment of tire pyrolysis feedstocks
Heterogeneous transfer learning for highly non-linear regression tasks with application to the hydrotreatment of tire pyrolysis feedstocks Open
International audience
View article: Heterogeneous Transfer Learning for Chemical Process Optimization: A Kinetics Perspective
Heterogeneous Transfer Learning for Chemical Process Optimization: A Kinetics Perspective Open
International audience
View article: Performance comparison of tire pyrolysis oils in hydrotreating toward high-quality fuel
Performance comparison of tire pyrolysis oils in hydrotreating toward high-quality fuel Open
View article: Comparative Performance of Machine Learning Architectures for Fault Detection and Diagnosis in Chemical Processes
Comparative Performance of Machine Learning Architectures for Fault Detection and Diagnosis in Chemical Processes Open
View article: Bayesian and subset-selection methods for parameter estimation in mechanistic models with limited data: A review and comparison
Bayesian and subset-selection methods for parameter estimation in mechanistic models with limited data: A review and comparison Open
View article: Enforcing Coherent Trends in a Continuous Lumping Models for Hydrocracking with Monte Carlo Markov Chains
Enforcing Coherent Trends in a Continuous Lumping Models for Hydrocracking with Monte Carlo Markov Chains Open
View article: Bayesian Transfer Learning with Monte Carlo Markov Chains for Kinetic Modelling of Pilot Plant and Industrial Data
Bayesian Transfer Learning with Monte Carlo Markov Chains for Kinetic Modelling of Pilot Plant and Industrial Data Open
View article: Applications of Monte Carlo Markov Chains in Kinetic Modelling of Hydroprocessing with Transfer Learning: Parameter Identification from Pilot Plant and Industrial Data
Applications of Monte Carlo Markov Chains in Kinetic Modelling of Hydroprocessing with Transfer Learning: Parameter Identification from Pilot Plant and Industrial Data Open
View article: Performance Comparison of Tire Pyrolysis Oils in Hydrotreating Toward High-Quality Fuel
Performance Comparison of Tire Pyrolysis Oils in Hydrotreating Toward High-Quality Fuel Open
View article: Reducing the Number of Experimental Points to Fit Kinetic Models: A Bayesian Approach
Reducing the Number of Experimental Points to Fit Kinetic Models: A Bayesian Approach Open
International audience
View article: Propagating input uncertainties into parameter uncertainties and model prediction uncertainties—A review
Propagating input uncertainties into parameter uncertainties and model prediction uncertainties—A review Open
A review of uncertainty quantification techniques is provided for a variety of situations involving uncertainties in model inputs (independent variables). The situations of interest are divided into three categories: (i) when model predict…
View article: Parameter estimation and prediction uncertainties for multi‐response kinetic models with uncertain inputs
Parameter estimation and prediction uncertainties for multi‐response kinetic models with uncertain inputs Open
Error‐in‐variables model (EVM) methods are used for parameter estimation when independent variables are uncertain. During EVM parameter estimation, output measurement variances are required as weighting factors in the objective function. T…
View article: Parameter estimation and prediction uncertainties for multi-response kinetic models with uncertain inputs
Parameter estimation and prediction uncertainties for multi-response kinetic models with uncertain inputs Open
Error-in-variables model (EVM) methods are used for parameter estimation when independent variables are uncertain. During EVM parameter estimation, output measurement variances are required as weighting factors in the objective function. T…
View article: Design of Experiment for Bayesian transferred model
Design of Experiment for Bayesian transferred model Open
International audience
View article: Reducing the Number of Experiments Required for Modelling the Hydrocracking Process with Kriging Through Bayesian Transfer Learning
Reducing the Number of Experiments Required for Modelling the Hydrocracking Process with Kriging Through Bayesian Transfer Learning Open
The objective is to improve the learning of a regression model of the hydrocracking process using a reduced number of observations. When a new catalyst is used for the hydrocracking process, a new model must be fitted. Generating new data …
View article: Modeling the hydrocracking process with kriging through Bayesian Transfer Learning
Modeling the hydrocracking process with kriging through Bayesian Transfer Learning Open
View article: Reducing the number of experiments required for modeling the hydrocracking process with kriging through Bayesian transfer learning
Reducing the number of experiments required for modeling the hydrocracking process with kriging through Bayesian transfer learning Open
View article: Bayesian inference for transfer learning
Bayesian inference for transfer learning Open
International audience
View article: Accelerating Kinetic Parameter Identification by Extracting Information from Transient Data: A Hydroprocessing Study Case
Accelerating Kinetic Parameter Identification by Extracting Information from Transient Data: A Hydroprocessing Study Case Open
Hydroprocessing reactions require several days to reach steady-state, leading to long experimentation times for collecting sufficient data for kinetic modeling purposes. The information contained in the transient data during the evolution …
View article: Stabilization time modeling for hydroprocessing: Identification of the dominant factors
Stabilization time modeling for hydroprocessing: Identification of the dominant factors Open
View article: Assessment of the dominant factors during hydroprocessing stabilization
Assessment of the dominant factors during hydroprocessing stabilization Open
View article: Comparing Kriging, Spline, and MLR in Product Properties Modelization: Application to Cloud Point Prediction
Comparing Kriging, Spline, and MLR in Product Properties Modelization: Application to Cloud Point Prediction Open
International audience
View article: Kriging Modeling to Predict Viscosity Index of Base Oils
Kriging Modeling to Predict Viscosity Index of Base Oils Open
International audience
View article: A single events microkinetic model for hydrocracking of vacuum gas oil
A single events microkinetic model for hydrocracking of vacuum gas oil Open
View article: A continuous lumping model for hydrocracking on a zeolite catalysts: model development and parameter identification
A continuous lumping model for hydrocracking on a zeolite catalysts: model development and parameter identification Open
View article: Parameter Fitting : which algorithm to choose ?
Parameter Fitting : which algorithm to choose ? Open
International audience