Objective: Based on the Bayesian network, this study investigates the impact pathways of multidimensional factors related to the living environment—specifically housing factors, exposure to daily ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

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 ...

1 School of Computer Science, Technological University Dublin, Dublin, Ireland 2 ADAPT Research Centre, School of Computer Science and Statistics, Trinity College Dublin, Dublin, Ireland Previous work ...

python scripts/bayesian_train.py --config [list of paths to configs to be merged, rightmost will override values of previous ones] Example: scripts/bayesian_train.py ...

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 ...