J. Pinto

A general deep hybrid model for bioreactor systems: Combining first principles with deep neural networks

Rafael S. Costa, R. Costa, G. Striedner, 2022, Comput. Chem. Eng..

A general deep hybrid model for bioreactor systems: combining first Principles equations with deep neural networks

Rafael S. Costa, R. Costa, G. Striedner, 2022, bioRxiv.

A General Hybrid Modeling Framework for Systems Biology Applications: Combining Mechanistic Knowledge with Deep Neural Networks under the SBML Standard

Rafael S. Costa, R. S. Costa, J. Pinto, 2023, AI.

SBML2HYB: a Python interface for SBML compatible hybrid modeling

R. S. Costa, Leonardo Alexandre, J. Pinto, 2023, Bioinformatics.

Hybrid Deep Modeling of a GS115 (Mut+) Pichia pastoris Culture with State–Space Reduction

Rafael S. Costa, R. S. Costa, J. Pinto, 2023, Fermentation.

A hierarchical hybrid neural model with time integrators in long-term load forecasting

Otávio Augusto S. Carpinteiro, Isaías Lima, Edmilson M. Moreira, 2009, Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005..

Deep hybrid modeling of a HEK293 process: Combining long short‐term memory networks with first principles equations

J. Pinto, Rui Oliveira, J. R. C. Ramos, 2024, Biotechnology and bioengineering.

Hybrid deep modeling of a CHO-K1 fed-batch process: combining first-principles with deep neural networks

J. Pinto, J. Ramos, Rui Oliveira, 2023, Frontiers in bioengineering and biotechnology.

A bootstrap-aggregated hybrid semi-parametric modeling framework for bioprocess development

M. von Stosch, Rui Oliveira, Cristiana Rodrigues de Azevedo, 2019, Bioprocess and Biosystems Engineering.