33 citations · 123 across the 12 of their papers we have counts for
Showing 2020 · physics.chem-phShow all
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physics.chem-ph2020★ 9 cited
Using the Gini coefficient to characterize the shape of computational chemistry error distributions
Pascal Pernot, Andreas Savin
The distribution of errors is a central object in the assesment and benchmarking of computational chemistry methods. The popular and often blind use of the mean unsigned error as a…
physics.chem-ph2020
Acknowledging user requirements for accuracy in computational chemistry benchmarks
Andreas Savin, Pascal Pernot
Computational chemistry has become an important complement to experimental measurements. In order to choose among the multitude of the existing approximations, it is common to use…
physics.chem-ph2020
Probabilistic performance estimators for computational chemistry methods: Systematic Improvement Probability and Ranking Probability Matrix. II. Applications
Pascal Pernot, Andreas Savin
In the first part of this study (Paper I), we introduced the systematic improvement probability (SIP) as a tool to assess the level of improvement on absolute errors to be expected…