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...
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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...
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...
Although cancer classification has improved over the past 30 years, there has been no general approach for identifying new cancer classes (class discovery) or for assigning tumo...
Preface Preface to the 2nd Edition 1. Human Science Introduction Why Do Human Science Research? What Is a Hermeneutic Phenomenological Human Science? What Does it Mean to Be Rat...
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...
Current research into semiconductor clusters is focused on the properties of quantum dots—fragments of semiconductor consisting of hundreds to many thousands of atoms—with the b...
Abstract Behavioral scientists routinely publish broad claims about human psychology and behavior in the world's top journals based on samples drawn entirely from Western, Educa...
Due to the safety risks and training sample inefficiency, it is often preferred to develop controllers in simulation. However, minor differences between the simulation and the r...
Abstract Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfi...
ABSTRACT A 16S rRNA gene database ( http://greengenes.lbl.gov ) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic cl...
While it is nearly effortless for humans to quickly assess the perceptual similarity between two images, the underlying processes are thought to be quite complex. Despite this, ...