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Modeling the hydrocracking process with kriging through Bayesian Transfer Learning

Title: Modeling the hydrocracking process with kriging through Bayesian Transfer Learning
Authors: Iapteff, Loïc; Jacques, Julien; Rolland, Matthieu; Celse, Benoît
Contributors: Entrepôts, Représentation et Ingénierie des Connaissances (ERIC); Université Lumière - Lyon 2 (UL2)-Université Claude Bernard Lyon 1 (UCBL); Université de Lyon-Université de Lyon; IFP Energies nouvelles (IFPEN)
Source: 2021 AIChE Virtual Spring Meeting and 17th Global Congress on Process Safety; https://hal.science/hal-03561361; 2021 AIChE Virtual Spring Meeting and 17th Global Congress on Process Safety, Apr 2021, virtual, United States
Publisher Information: CCSD
Publication Year: 2021
Collection: Portail HAL de l'Université Lumière Lyon 2
Subject Terms: Transfer Knowledge of Parameters; Regression modeling; Gaussian Process; MCMC algorithm; Kriging; [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]
Subject Geographic: virtual; United States
Description: International audience
Document Type: conference object
Language: English
Availability: https://hal.science/hal-03561361; https://hal.science/hal-03561361v1/document; https://hal.science/hal-03561361v1/file/abstract_BayesianTL_AIChE.pdf
Rights: https://about.hal.science/hal-authorisation-v1/ ; info:eu-repo/semantics/OpenAccess
Accession Number: edsbas.913CAAB2
Database: BASE