HAL (France)
open access
Enforcing coherent trends in a continuous lumping models for hydrocracking with Monte Carlo Markov Chains
We present an extended Bayesian Transfer Learning framework that integrates heterogeneous data sources for developing robust kinetic models in industrial catalyst development. The methodology incorporates hard and soft constraints into Monte Carlo Markov Chain (MCMC) sampling, enabling multi-objecti
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