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The Journal of Chemical Physics|May 3, 2020
Probabilistic performance estimators for computational chemistry methods: Systematic improvement probability and ranking probability matrix. II. ApplicationsPascal Pernot, Andreas SavinThe Journal of Chemical Physics|May 3, 2020
Probabilistic performance estimators for computational chemistry methods: Systematic improvement probability and ranking probability matrix. I. TheoryPascal Pernot, Andreas SavinThe Journal of Chemical Physics|July 2, 2018
Probabilistic performance estimators for computational chemistry methods: The empirical cumulative distribution function of absolute errorsPascal Pernot, Andreas SavinThe Journal of Physical Chemistry. A|January 29, 2015
Prediction uncertainty of density functional approximations for properties of crystals with cubic symmetryPascal Pernot, Bartolomeo Civalleri, Davide Presti, et al.Journal of Molecular Modeling|February 11, 2017
When does a functional correctly describe both the structure and the energy of the transition state?Neil Qiang Su, Pascal Pernot, Xin Xu, et al.The Journal of Chemical Physics|September 17, 2017
The parameter uncertainty inflation fallacyPascal PernotThe Journal of Chemical Physics|March 23, 2022
The long road to calibrated prediction uncertainty in computational chemistryPascal PernotThe Journal of Chemical Physics|October 15, 2022
Prediction uncertainty validation for computational chemistsPascal PernotThe Journal of Chemical Physics|February 10, 2011
Statistical approaches to forcefield calibration and prediction uncertainty in molecular simulationFabien Cailliez, Pascal PernotThe Journal of Physical Chemistry. A|April 19, 2007
Modeling of branching ratio uncertainty in chemical networks by Dirichlet distributionsNathalie Carrasco, Pascal PernotPageof 9