Now showing items 6-9 of 9

    • Gaussian Approximation Potentials: a brief tutorial introduction 

      Bartók, Albert P.; Csányi, Gábor (Wiley, 2015-04-27)
      We present a swift walk-through of our recent work that uses machine learning to t interatomic potentials based on quantum mechanical data. We describe our Gaussian Approximation Potentials (GAP) framework, discuss a ...
    • Jumping the Gun: Mapping Neural Correlates of Waiting Impulsivity and Relevance 

      Morris, Laurel S.; Kundu, Prantik; Baek, Kwangyeol; Irvine, Michael A.; Mechelmans, Daisy J.; Wood, Jonathan; Harrison, Neil A. et al. (Elsevier, 2015-06-12)
      Background: Why do we ‘jump the gun’ or speak out of turn? Waiting impulsivity has a preclinical basis as a predictor for the development of addiction. Here we mapped the intrinsic neural correlates of waiting and dissociate ...
    • Predicting beneficial effects of atomoxetine and citalopram on response inhibition in Parkinson’s disease with clinical and neuroimaging measures 

      Ye, Zheng; Rae, Charlotte L.; Nombela, Cristina; Ham, Timothy; Rittman, Timothy; Jones, Peter Simon; Vázquez Rodríguez, Patricia et al. (Wiley, 2016-01-12)
      Recent studies indicate that selective noradrenergic (atomoxetine) and serotonergic (citalopram) reuptake inhibitors may improve response inhibition in selected patients with Parkinson's disease, restoring behavioral ...
    • Web-based machine learning models for real-time screening of thermoelectric materials properties 

      Gaultois, Michael W.; Oliynyk, Anton O.; Mar, Arthur; Sparks, Taylor D.; Mulholland, Gregory J.; Meredig, Bryce (American Institute of Physics, 2016)
      The experimental search for new thermoelectric materials remains largely confined to a limited set of successful chemical and structural families, such as chalcogenides, skutterudites, and Zintl phases. In principle, ...