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20022025
most citedSystematic comparison of force fields for microscopic simulations of NaCl in aqueous solutions: Diffusion, free energy of hydration and structural properties

206 citations

Showing 2023Show all

13 papers · 1 filter

math.LO2023★ 2 cited

Axiomatizing modal inclusion logic and its variants

Aleksi Anttila, Matilda Häggblom, Fan Yang

We provide a complete axiomatization of modal inclusion logic - team-based modal logic extended with inclusion atoms. We review and refine an expressive completeness and normal for…

math.AP2023

Monotone approximation of differentiable convex functions with applications to general minimization problems

Petteri Harjulehto, Peter Hästö, Andrea Torricelli

We study minimizers of non-autonomous energies with minimal growth and coercivity assumptions on the energy. We show that the minimizer is nevertheless the solution of the relevant…

math.FA2023★ 5 cited

A revised condition for harmonic analysis in generalized Orlicz spaces on unbounded domains

Petteri Harjulehto, Peter Hästö, Artur Słabuszewski

Conditions for harmonic analysis in generalized Orlicz spaces have been studied over the past decade. One approach involves the generalized inverse of so-called weak -functions.…

math.ST2023

The Asymptotic Properties of the One-Sample Spatial Rank Methods

Jyrki Möttönen, Klaus Nordhausen, Hannu Oja +1

For a set of -variate data points , there are several versions of multivariate median and related multivariate sign test proposed and stu…

cond-mat.mtrl-sci2023

Inner product regularized multi-energy X-ray tomography for material decomposition

Salla-Maaria Latva-Äijö, Filippo Zanetti, Ari-Pekka Honkanen +4

Multi-energy X-ray tomography is studied for decomposing three materials using three X-ray energies and a classical energy-integrating detector. A novel regularization term compris…

math.ST2023★ 3 cited

Comparing Scale Parameter Estimators for Gaussian Process Interpolation with the Brownian Motion Prior: Leave-One-Out Cross Validation and Maximum Likelihood

Masha Naslidnyk, Motonobu Kanagawa, Toni Karvonen +1

Gaussian process (GP) regression is a Bayesian nonparametric method for regression and interpolation, offering a principled way of quantifying the uncertainties of predicted functi…