Squeeze-and-Excitation Networks
Convolutional neural networks are built upon the convolution operation, which extracts informative features by fusing spatial and channel-wise information together within local ...
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Convolutional neural networks are built upon the convolution operation, which extracts informative features by fusing spatial and channel-wise information together within local ...
Large phylogenomics data sets require fast tree inference methods, especially for maximum-likelihood (ML) phylogenies. Fast programs exist, but due to inherent heuristics to fin...
The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collabor...
Abstract The paper explores the usefulness of analysing firms from the resource side rather than from the product side. In analogy to entry barriers and growth‐share matrices, t...
Leon Festinger's theory of cognitive dissonance has been widely recognized for its important and influential concepts in areas of motivation and social psychology. The theory of...
Suppose x is an unknown vector in Ropf <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">m</sup> (a digital image or signal); we pla...
A new approach to the construction of first-principles pseudopotentials is described. The method allows transferability to be improved systematically while holding the cutoff ra...
Generalized gradient approximations (GGA’s) seek to improve upon the accuracy of the local-spin-density (LSD) approximation in electronic-structure calculations. Perdew and Wang...
Traditional econometric models assume a constant one-period forecast variance. To generalize this implausible assumption, a new class of stochastic processes called autoregressi...
Cooperation in organisms, whether bacteria or primates, has been a difficulty for evolutionary theory since Darwin. On the assumption that interactions between pairs of individu...