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Fidelity, dynamic structure factor, and susceptibility in critical phenomena

Physical review. E, Statistical, nonlinear, and soft matter physics, 2007-08, Vol.76 (2 Pt 1), p.022101-022101, Article 022101

2007

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Generic, hierarchical framework for massively parallel Wang-Landau sampling

Physical review letters, 2013-05, Vol.110 (21), p.210603-210603, Article 210603

2013

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Machine-learning-assisted insight into spin ice Dy2Ti2O7

Nature communications, 2020-02, Vol.11 (1), p.892-892, Article 892

2020

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Stable stem enabled Shannon entropies distinguish non-coding RNAs from random backgrounds

BMC bioinformatics, 2012-04, Vol.13 Suppl 5 (S5), p.S1-S1, Article S1

2012

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Calpain and N-methyl- d-aspartate (NMDA)-induced excitotoxicity in rat retinas

Brain research, 2005-06, Vol.1046 (1), p.207-215

2005

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Hands-on with OWL: the Oak–Ridge Wang–Landau Monte Carlo software suite

Journal of physics. Conference series, 2021-11, Vol.2122 (1), p.12001

2021

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A practical guide to replica-exchange Wang-Landau simulations

Journal of physics. Conference series, 2018, Vol.1012 (1), p.12003

2018

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Green tea extract treatment alleviates ocular inflammation in a rat model of endotoxin-induced uveitis

PloS one, 2014-08, Vol.9 (8), p.e103995

2014

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Effects of EGCG content in green tea extract on pharmacokinetics, oxidative status and expression of inflammatory and apoptotic genes in the rat ocular tissues

The Journal of nutritional biochemistry, 2015-11, Vol.26 (11), p.1357-1367

2015

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Effect of single-site mutations on hydrophobic-polar lattice proteins

Physical review. E, Statistical, nonlinear, and soft matter physics, 2014-09, Vol.90 (3), p.033307-033307, Article 033307

2014

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Green Tea Catechins and Their Oxidative Protection in the Rat Eye

Journal of agricultural and food chemistry, 2010-02, Vol.58 (3), p.1523-1534

2010

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Monte Carlo simulations of the HP model (the “Ising model” of protein folding)

Computer physics communications, 2011-09, Vol.182 (9), p.1896-1899

2011

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Scalable replica-exchange framework for Wang-Landau sampling

Physical review. E, Statistical, nonlinear, and soft matter physics, 2014-08, Vol.90 (2), p.023302-023302, Article 023302

2014

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Conformational transitions of a confined lattice protein: A Wang-Landau study

Journal of physics. Conference series, 2012-12, Vol.402 (1), p.12048-8

2012

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Generic folding and transition hierarchies for surface adsorption of hydrophobic-polar lattice model proteins

Physical review. E, Statistical, nonlinear, and soft matter physics, 2013-01, Vol.87 (1), p.012706-012706, Article 012706

2013

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Fast and stable deep-learning predictions of material properties for solid solution alloys

Journal of physics. Condensed matter, 2021-02, Vol.33 (8), p.084005-084005

2021

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The Rise of Neural Networks for Materials and Chemical Dynamics

The journal of physical chemistry letters, 2021-07, Vol.12 (26), p.6227-6243

2021

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A scalable algorithm for the optimization of neural network architectures

Parallel computing, 2021-04, Vol.104-105

2021

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QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

Journal of physics. Condensed matter, 2018-05, Vol.30 (19), p.195901-195901

2018

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Fast and stable deep-learning predictions of material properties for solid solution alloys This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do s

Journal of physics. Condensed matter, 2020-12, Vol.33 (8)

2020

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Histogram-free multicanonical Monte Carlo sampling to calculate the density of states

Computer physics communications, 2018-10, Vol.235 (C)

2018

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Towards an accurate description of perovskite ferroelectrics: exchange and correlation effects

Scientific reports, 2017-03, Vol.7 (1), p.43482-10, Article 43482

2017

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Synergy of semiempirical models and machine learning in computational chemistry

The Journal of chemical physics, 2023-09, Vol.159 (11)

2023

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A scalable algorithm for the optimization of neural network architectures

Parallel computing, 2021-07, Vol.104-105, p.102788, Article 102788

2021

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Performance Analysis of CP2K Code for Ab Initio Molecular Dynamics on CPUs and GPUs

Journal of chemical information and modeling, 2022-05, Vol.62 (10), p.2378-2386

2022

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Fidelity, dynamic structure factor, and susceptibility in critical phenomena

Generic, hierarchical framework for massively parallel Wang-Landau sampling

Machine-learning-assisted insight into spin ice Dy2Ti2O7

Stable stem enabled Shannon entropies distinguish non-coding RNAs from random backgrounds

Calpain and N-methyl- d-aspartate (NMDA)-induced excitotoxicity in rat retinas

Hands-on with OWL: the Oak–Ridge Wang–Landau Monte Carlo software suite

A practical guide to replica-exchange Wang-Landau simulations

Green tea extract treatment alleviates ocular inflammation in a rat model of endotoxin-induced uveitis

Effects of EGCG content in green tea extract on pharmacokinetics, oxidative status and expression of inflammatory and apoptotic genes in the rat ocular tissues

Effect of single-site mutations on hydrophobic-polar lattice proteins

Green Tea Catechins and Their Oxidative Protection in the Rat Eye

Monte Carlo simulations of the HP model (the “Ising model” of protein folding)

Scalable replica-exchange framework for Wang-Landau sampling

Conformational transitions of a confined lattice protein: A Wang-Landau study

Generic folding and transition hierarchies for surface adsorption of hydrophobic-polar lattice model proteins

Fast and stable deep-learning predictions of material properties for solid solution alloys

The Rise of Neural Networks for Materials and Chemical Dynamics

A scalable algorithm for the optimization of neural network architectures

QMCPACK: an open source ab initio quantum Monte Carlo package for the electronic structure of atoms, molecules and solids

Histogram-free multicanonical Monte Carlo sampling to calculate the density of states

Towards an accurate description of perovskite ferroelectrics: exchange and correlation effects

Synergy of semiempirical models and machine learning in computational chemistry

A scalable algorithm for the optimization of neural network architectures

Performance Analysis of CP2K Code for Ab Initio Molecular Dynamics on CPUs and GPUs

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