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Estimating wage disparities using foundation models. [PDF]
Proc Natl Acad Sci U S AVafa K, Athey S, Blei DM.
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Optimizing sample size for supervised machine learning with bulk transcriptomic sequencing: a learning curve approach. [PDF]
Brief BioinformQi Y, Wang X, Qin LX.
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Minimizing Bleed-Through Effect in Medieval Manuscripts with Machine Learning and Robust Statistics
Adriano Ettari +4 more
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Statistics, machine learning and deep learning for population genetic inference
, 2021Deciphering the evolutionary changes from raw DNA data effectively without the loss of intrinsic information has been the fundamental and core work in population genetics. However, some statistical challenges still restrict the inferential performance in
Xinghu Qin
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Statistics, Machine Learning, and Data Science: A Historical Review and a Look to the Future
Conference on Research, Innovation and Vision for the Future in Computing & Communication Technologies, 2023We are witnessing the beginning of a data driven era with the explosion of data, impact of data on our everyday lives, and advances of data processing methodology and technology. At this juncture, data science has emerged as an interdisciplinary field to
Tru Cao
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The Matérn Model: A Journey Through Statistics, Numerical Analysis and Machine Learning
Statistical Science, 2023The Mat\'ern model has been a cornerstone of spatial statistics for more than half a century. More recently, the Mat\'ern model has been central to disciplines as diverse as numerical analysis, approximation theory, computational statistics, machine ...
E. Porcu +3 more
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Machine Learning and Statistics in Clinical Research Articles-Moving Past the False Dichotomy.
JAMA pediatrics, 2023This Viewpoint describes the false dichotomy between statistics and machine learning and suggests considerations in building and evaluating clinical prediction models.
S. G. Finlayson, A. Beam, M. van Smeden
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Statistics meets Machine Learning
Oberwolfach Reports, 2021Theory and application go hand in hand in most areas of statistics. In a world flooded with huge amounts of data waiting to be analyzed, classified and transformed into useful outputs, the designing of fast, robust and stable algorithms has never been as important as it is today. On the other hand, irrespective of whether the focus is put on estimation,
Lutz Dümbgen +3 more
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