Representation Learning: A Review and New Perspectives
The success of machine learning algorithms generally depends on data representation, and we hypothesize that this is because different representations can entangle and hide more...
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An Introduction to Fluid Dynamics
First published in 1967, Professor Batchelor's classic text on fluid dynamics is still one of the foremost texts in the subject. The careful presentation of the underlying theor...
Linear Models and Empirical Bayes Methods for Assessing Differential Expression in Microarray Experiments
The problem of identifying differentially expressed genes in designed microarray experiments is considered. Lonnstedt and Speed (2002) derived an expression for the posterior od...
A Mathematical Theory of Evidence
Both in science and in practical affairs we reason by combining facts only inconclusively supported by evidence. Building on an abstract understanding of this process of combina...
Generative adversarial networks
Generative adversarial networks are a kind of artificial intelligence algorithm designed to solve the generative modeling problem. The goal of a generative model is to study a c...
Modularity and community structure in networks
Many networks of interest in the sciences, including social networks, computer networks, and metabolic and regulatory networks, are found to divide naturally into communities or...
Structure, function and diversity of the healthy human microbiome
Studies of the human microbiome have revealed that even healthy individuals differ remarkably in the microbes that occupy habitats such as the gut, skin and vagina. Much of this...
Photocatalysis on TiO2 Surfaces: Principles, Mechanisms, and Selected Results
ADVERTISEMENT RETURN TO ISSUEPREVArticleNEXTPhotocatalysis on TiO2 Surfaces: Principles, Mechanisms, and Selected ResultsAmy L. Linsebigler, Guangquan Lu, and John T. Yates Jr.C...