ABSTRACT: This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...
Abstract: Bayesian networks are widely used for causal discovery and probabilistic modeling across diverse domains including healthcare, multi-dimensional data analysis, environmental modeling, and ...
Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body's chemistry and each ...
Single-cell transcriptomic architecture for deciphering the complexity of tumor microenvironment in ampulla of Vater carcinoma. Advancing treatment outcomes for peritoneal surface malignancies in low- ...
Introduction: During the commissioning and operation of shale gas pipelines, multiple perforation accidents caused by internal corrosion have occurred. Research on internal corrosion probability ...
Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...
Department of Computational and Quantitative Medicine, Beckman Research Institute of the City of Hope, 1218 S 5th Ave, Monrovia, California 91016, United States Irell and Manella Graduate School of ...
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