Results 191 to 200 of about 866,116 (323)

gp-gam-optimisation-dataset: Example input and output data for Gaussian Process and GAM workflow (H₂SO₄, January 2017)

Ghosh, Kunal, Regayre, Leighton A.
openalex   +1 more source

Understanding the Role of Superhydrophobicity and Superhydrophilicity in Salt‐Spray Corrosion of Nanosecond Pulsed Laser‐Textured AA2024 Alloy

Advanced Functional Materials, EarlyView.
Nanosecond pulse laser texturing yields superhydrophobic and superhydrophilic AA2024 surfaces. Salt‐spray tests show that periodic superhydrophobic patterns suppress pitting, whereas superhydrophilic textures enhance it, linking laser‐induced morphology, wettability, and oxide chemistry to corrosion resistance.
Lis Geraldine Zschach, Robert Baumann, Eric Pohl, Angelika Wrzesińska‐Lashkova, Marcelo Sallese, Ignacio Tabares, Herman Heffner, Yana Vaynzof, Andrés Fabián Lasagni   +8 more
wiley   +1 more source

Bayesian parameter inference and uncertainty quantification for a computational pulmonary hemodynamics model using Gaussian processes. [PDF]

Comput Biol Med
Kachabi A, Altieri Correa S, Chesler NC, Colebank MJ.   +3 more
europepmc   +1 more source

Exact Gaussian processes for massive datasets via non-stationary sparsity-discovering kernels. [PDF]

Sci Rep, 2023
Noack MM, Krishnan H, Risser MD, Reyes KG.   +3 more
europepmc   +1 more source

Deep Gaussian Process Emulation using Stochastic Imputation

, 2022
Deyu Ming, Daniel Williamson, Serge Guillas   +2 more
openalex   +1 more source

Beyond the Edge: Charge‐Transfer Excitons in Organic Donor‐Acceptor Cocrystals

Advanced Functional Materials, EarlyView.
Complex excitonic landscapes in acene–perfluoroacene cocrystals are unveiled by polarization‐resolved optical spectroscopy and many‐body theory. This systematic study of a prototypical model system for weakly interacting donor–acceptor compounds challenges common views of charge‐transfer excitons, providing a refined conceptual framework for ...
Sebastian Anhäuser, Ana M. Valencia, Sergei I. Ivlev, Marc Zeplichal, Andreas Terfort, Caterina Cocchi, Gregor Witte   +6 more
wiley   +1 more source

Bayesian Optimization with Gaussian Processes Assisted by Deep Learning for Material Designs. [PDF]

J Phys Chem Lett
Kiyohara S, Kumagai Y.
europepmc   +1 more source

An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells. [PDF]

Bioinformatics, 2023
Sahay S, Adhikari S, Hormoz S, Chakrabarti S.   +3 more
europepmc   +1 more source

Photon Avalanching Nanoparticles: The Next Generation of Upconverting Nanomaterials?

Advanced Functional Materials, EarlyView.
This Perspective outlines the mechanistic foundations that enable photon‐avalanche (PA) behavior in lanthanide nanomaterials and contrasts them with emerging application spaces and forward‐looking design strategies. By bridging threshold engineering, energy‐transfer dynamics, and materials engineering, we provide a coherent roadmap for advancing the ...
Kimoon Lee, Yunseo Kim, Hyeong‐ku Jo, Dongjoon Yoon, Byeonghyeok Im, WonJeong Yu, Eui‐Rim On, Changhwan Lee   +7 more
wiley   +1 more source

Integrating Cacao Physicochemical-Sensory Profiles via Gaussian Processes Crowd Learning and Localized Annotator Trustworthiness. [PDF]

Foods
Lugo-Rojas JC, Chica-Morales MJ, Florez-González SL, Álvarez-Meza AM, Castellanos-Dominguez G.   +4 more
europepmc   +1 more source