Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley +1 more source
A guide to bayesian networks software for structure and parameter learning, with a focus on causal discovery tools. [PDF]
Canonaco F +4 more
europepmc +1 more source
Inferring Dynamic Bayesian Networks using Frequent Episode Mining [PDF]
Debprakash Patnaik +2 more
openalex +1 more source
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee +3 more
wiley +1 more source
Integrating Machine Learning and Dynamic Bayesian Networks to Identify the Factors Associated with Subsequent Intrapulmonary Metastasis Classification After Initial Single Primary Lung Cancer. [PDF]
Liu W +6 more
europepmc +1 more source
Tractable Bayesian Learning of Tree Belief Networks [PDF]
Marina Meilă, Tommi Jaakkola
openalex +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Bayesian networks and structural equation models reveal genetic causal relationships between productivity, defense, and climate-adaptability traits in interior lodgepole pine. [PDF]
Cappa EP +7 more
europepmc +1 more source
Eliciting Bayesian networks via online surveys: a new approach to knowledge elicitation
Peter Edgar Serwylo
openalex +2 more sources
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source

