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Gradient-based learning applied to document recognition
Multilayer neural networks trained with the back-propagation algorithm constitute the best example of a successful gradient based learning technique. Given an appropriate networ...
Density-functional exchange-energy approximation with correct asymptotic behavior
Current gradient-corrected density-functional approximations for the exchange energies of atomic and molecular systems fail to reproduce the correct 1/r asymptotic behavior of t...
The CES-D Scale
The CES-D scale is a short self-report scale designed to measure depressive symptomatology in the general population. The items of the scale are symptoms associated with depress...
Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks
Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified con...
UCSF Chimera—A visualization system for exploratory research and analysis
Abstract The design, implementation, and capabilities of an extensible visualization system, UCSF Chimera, are discussed. Chimera is segmented into a core that provides basic se...
Going deeper with convolutions
We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the ImageNet Large-Sca...
EMBI
Requirements are an integral part of industry operation and projects. Not only do requirements dictate industrial operations, but they are used in legally binding contracts betw...
The Hospital Anxiety and Depression Scale
ABSTRACT– A self‐assessment scale has been developed and found to be a reliable instrument for detecting states of depression and anxiety in the setting of an hospital medical o...