Fine‐tuning ab initio XANES spectra calculations using the Bayesian optimization algorithm
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
Riemannian L-systems: modelling growing forms in curved spaces. [PDF]
Godin C, Boudon F.
europepmc +1 more source
Hierarchical organization of rhesus macaque behavior. [PDF]
Voloh B +6 more
europepmc +1 more source
Calibrating Bayesian inference
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]
Zsido AN +8 more
europepmc +1 more source
A mathematical framework for the analysis and comparison of contact detection methods for ellipses and ellipsoids. [PDF]
Kheradmand E, Laforest M, Prudhomme S.
europepmc +1 more source
FluidMap: Proportional and Spatially Consistent Layout Enrichments in Multidimensional Projections
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
A Geometry of Hamiltonian Mechanics. [PDF]
Elgressy G, Horwitz L.
europepmc +1 more source
SDFs from Unoriented Point Clouds using Neural Variational Heat Distances
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]
Müller C +9 more
europepmc +1 more source

