When Bioprocess Engineering Meets Machine Learning: A Survey from the Perspective of Automated Bioprocess Development

no code implementations • 2 Sep 2022 • Nghia Duong-Trung, Stefan Born, Jong Woo Kim, Marie-Therese Schermeyer, Katharina Paulick, Maxim Borisyak, Mariano Nicolas Cruz-Bournazou, Thorben Werner, Randolf Scholz, Lars Schmidt-Thieme, Peter Neubauer, Ernesto Martinez

ML can be seen as a set of tools that contribute to the automation of the whole experimental cycle, including model building and practical planning, thus allowing human experts to focus on the more demanding and overarching cognitive tasks.

Model Selection Probabilistic Programming