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...
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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...
Systematic reviews and meta-analyses have become increasingly important in health care. Clinicians read them to keep up to date with their field,1,2 and they are often used as a...
We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting,...
We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existi...
Understanding sources of sustained competitive advantage has become a major area of research in strategic management. Building on the assumptions that strategic resources are he...
Recent work has shown that convolutional networks can be substantially deeper, more accurate, and efficient to train if they contain shorter connections between layers close to ...
Classical Monte Carlo simulations have been carried out for liquid water in the NPT ensemble at 25 °C and 1 atm using six of the simpler intermolecular potential functions for t...
Abstract Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort ...
Part I: Introduction to Grounded Theory of Anselm Strauss Chapter 1: Inspiration and Background Chapter 2: Theoretical Foundations Chapter 3: Practical Considerations for Gettin...
Understanding sources of sustained competitive advantage has become a major area of research in strategic management. Building on the assumptions that strategic resources are he...
A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is ...
Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end, pixels-to-pixels, ex...