The chemistry of graphene oxide
The chemistry of graphene oxide is discussed in this critical review. Particular emphasis is directed toward the synthesis of graphene oxide, as well as its structure. Graphene ...
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The chemistry of graphene oxide is discussed in this critical review. Particular emphasis is directed toward the synthesis of graphene oxide, as well as its structure. Graphene ...
Growing Graphene The highest quality graphene samples, single-atom-thick layers of carbon, are suspended flakes exfoliated from graphite, but these samples are very small in siz...
The Coding Manual fourth edition is reformatted to 15 chapters and divided into three parts, as opposed to six chapters in the third edition.This provides readers with more stra...
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, ...
Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations as a generic family...
By decomposing the image formation process into a sequential application of denoising autoencoders, diffusion models (DMs) achieve state-of-the-art synthesis results on image da...
The author presents a conceptual model of brand equity from the perspective of the individual consumer. Customer-based brand equity is defined as the differential effect of bran...
Benjamini and Hochberg suggest that the false discovery rate may\nbe the appropriate error rate to control in many applied multiple testing\nproblems. A simple procedure was giv...
Time underlies many interesting human behaviors. Thus, the question of how to represent time in connectionist models is very important. One approach is to represent time implici...
Networking together hundreds or thousands of cheap microsensor nodes allows users to accurately monitor a remote environment by intelligently combining the data from the individ...
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...