Faculty develop methods for structured and unstructured biomedical data that advance statistical inference, machine learning, causal inference, and algorithmic modeling. Their work delivers principled ...

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 ...

Statistics professor Johan Ferreira was feeling overwhelmed by the amount of “screen time” involved in online learning in 2021. He imagined students must be feeling the same way, and wondered what he ...

This important study is of relevance for the fields of predictive processing, perception and learning, with a well-designed paradigm allowing the authors to avoid several common confounds in ...

In education, as in psychology, clarity matters. Yet in everyday conversations about teaching and learning, terms like learning theory and pedagogy are often used interchangeably. Phrases such as “We ...

The analysis of covariance (Ancova) is a widely used statistical technique for the comparison of groups with respect to a quantitative dependent variable in such a way that the comparison takes into ...

Statistical learning (SL) is a fundamental cognitive ability enabling individuals to detect and exploit regularities in environmental input. It plays a crucial role in language acquisition, perceptual ...

Department of Chemical and Biological Engineering, University of Wisconsin, Madison, Wisconsin 53706, United States Department of Materials Science and Engineering, University of Wisconsin, Madison, ...

FSML (Fortran Statistics and Machine Learning) is a scientific toolkit consisting of common statistical and machine learning procedures, including basic statistics (e.g., mean, variance, correlation), ...