Results 101 to 110 of about 289 (170)

Fine‐tuning ab initio XANES spectra calculations using the Bayesian optimization algorithm

open access: yesJournal of Synchrotron Radiation, EarlyView.
A Bayesian optimization technique is used to tune the FEFF and FDMNES packages and to improve matching between theoretical and experimental spectra. The tests were performed on monometallic Ni, Fe and Pd K‐edge XANES spectra using several different spectrum similarity metrics.Theoretical modeling of X‐ray absorption near‐edge structure (XANES) spectra ...
Andrey A. Sapronov   +2 more
wiley   +1 more source

Hierarchical organization of rhesus macaque behavior. [PDF]

open access: yesOxf Open Neurosci, 2023
Voloh B   +6 more
europepmc   +1 more source

Calibrating Bayesian inference

open access: yesBritish Journal of Mathematical and Statistical Psychology, EarlyView.
Abstract Bayesian statistics has gained popularity in psychological research due to its intuitive uncertainty quantification and convenient information‐updating rules. In many applications, however, prior distributions are introduced merely as instruments to facilitate computation, rather than as representations of genuine subjective belief ...
Yang Liu   +2 more
wiley   +1 more source

ThreatSim: A novel stimuli database of threatening and nonthreatening image pairs rated for similarity. [PDF]

open access: yesBehav Res Methods
Zsido AN   +8 more
europepmc   +1 more source

FluidMap: Proportional and Spatially Consistent Layout Enrichments in Multidimensional Projections

open access: yesComputer Graphics Forum, EarlyView.
FluidMap faithfully represents the frequency of an attribute and preserves spatial consistency. Current space‐filling methods over‐ or under‐represent attribute categories (i.e., all Voronoi‐based methods), sacrifice spatial consistency (i.e., Nmap) or both (i.e., Voronoi‐MWα).
Daniela Blumberg   +5 more
wiley   +1 more source

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

open access: yesComputer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier   +5 more
wiley   +1 more source

Machine learning for nonadiabatic molecular dynamics: best practices and recent progress. [PDF]

open access: yesChem Sci
Müller C   +9 more
europepmc   +1 more source

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