466 citations · 2.4k across the 48 of their papers we have counts for
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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…
On connecting density functional approximations to theory
Andreas Savin
Usually, density functional models are considered approximations to density functional theory, However, there is no systematic connection between the two, and this can make us doub…
Models and corrections: range separation for electronic interaction -- lessons from density functional theory
Andreas Savin
Model Hamiltonians with long-range interaction yield energies that are corrected taking into account the universal behavior of the electron-electron interaction at short range. Alt…
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…
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…