<i>Ab initio</i>molecular dynamics for liquid metals
We present ab initio quantum-mechanical molecular-dynamics calculations based on the calculation of the electronic ground state and of the Hellmann-Feynman forces in the local-d...
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Densely Connected Convolutional Networks
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 ...
XGBoost
Tree boosting is a highly effective and widely used machine learning method.\nIn this paper, we describe a scalable end-to-end tree boosting system called\nXGBoost, which is use...
Three Approaches to Qualitative Content Analysis
Content analysis is a widely used qualitative research technique. Rather than being a single method, current applications of content analysis show three distinct approaches: con...
An Inventory for Measuring Depression
The difficulties inherent in obtaining consistent and adequate diagnoses for the purposes of research and therapy have been pointed out by a number of authors. Pasamanick<sup>12...
Multiple regression: testing and interpreting interactions
Introduction Interactions between Continuous Predictors in Multiple Regression The Effects of Predictor Scaling on Coefficients of Regression Equations Testing and Probing Three...
Equation of State Calculations by Fast Computing Machines
A general method, suitable for fast computing machines, for investigating such properties as equations of state for substances consisting of interacting individual molecules is ...
Fully convolutional networks for semantic segmentation
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...