Gaussian Processes for Machine Learning
We give a basic introduction to Gaussian Process regression models. We focus on understanding the role of the stochastic process and how it is used to define a distribution over...
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We give a basic introduction to Gaussian Process regression models. We focus on understanding the role of the stochastic process and how it is used to define a distribution over...
The challenges for further development of Li rechargeable batteries for electric vehicles are reviewed. Most important is safety, which requires development of a nonflammable el...
Prediction tasks over nodes and edges in networks require careful effort in engineering features used by learning algorithms. Recent research in the broader field of representat...
Singular integrals are among the most interesting and important objects of study in analysis, one of the three main branches of mathematics. They deal with real and complex numb...
<b><i>Background:</i></b> We aimed to investigate the influence of oligomeric forms of β-amyloid (Aβ) and the influence of the duration of exposure on th...
This is the first volume of the proposed many-sectioned "Handbook" in which the American Physiological Society intends to present comprehensively the entire field of physiology....
ABSTRACT The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), ...
Posttraumatic stress disorder is more prevalent than previously believed, and is often persistent. Progress in estimating age-at-onset distributions, cohort effects, and the con...