Results 121 to 130 of about 165,261 (262)
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
Bayesian Estimation of Marginal Quantiles with Missing Data in a Multivariate Regression Framework. [PDF]
Morán-Vásquez RA +2 more
europepmc +1 more source
Mechanisms of Alkali Ionic Transport in Amorphous Oxyhalides Solid State Conductors
Large‐scale machine learning‐based molecular dynamics simulations are used to investigate isovalent amorphous oxyhalides, revealing a remarkable chemically independent ionic conductivity. A rigorous analysis of alkali residence times across different metal–anion environments identifies divalent anions as key diffusion bottlenecks.
Luca Binci +3 more
wiley +1 more source
Bayesian Estimation Improves Prediction of Outcomes After Epilepsy Surgery. [PDF]
Dickey AS +4 more
europepmc +1 more source
Bayesian computational methods [PDF]
If, in the mid 1980?s, one had asked the average statistician about the difficulties of using Bayesian Statistics, his/her most likely answer would have been ?Well, there is this problem of selecting a prior distribution and then, even if one agrees on ...
Robert, Christian P.
core
Kinetic–energetic projection of time‐resolved photoluminescence reveals that charge‐transfer injection acts as a universal bottleneck in organic solar cells. A physics‐constrained Bayesian framework identifies an emergent effective CT injection rate governing the trade‐off between charge generation and nonradiative energy loss.
Rong Wang +16 more
wiley +1 more source
Bayesian estimation yields anti-Weber variability. [PDF]
Prat-Carrabin A, Gershman SJ.
europepmc +1 more source
Rates of convergence for the posterior distributions of mixtures of Betas and adaptive nonparametric estimation of the density. [PDF]
In this paper, we investigate the asymptotic properties of nonparametric Bayesian mixtures of Betas for estimating a smooth density on [0, 1]. We consider a parametrization of Beta distributions in terms of mean and scale parameters and construct a ...
Rousseau, Judith
core
Abstract This study examines producer participation choices considering a variety of potential benefits linked to state‐sponsored marketing programs, using a real choice dataset of farmers in Missouri. Multinomial logit models are employed to predict determinants of farmer enrollment in three tiers of the Missouri Grown local food marketing program ...
Lan Tran, Ye Su, Laura McCann
wiley +1 more source
Bayesian estimation of covariate assisted principal regression for brain functional connectivity. [PDF]
Park HG.
europepmc +1 more source

