Results 181 to 190 of about 851,390 (284)

Sensitivity Analysis of RV Reducer Rotation Error Based on Deep Gaussian Processes. [PDF]

Sensors (Basel), 2023
Jin S, Shang S, Jiang S, Cao M, Wang Y.
europepmc   +1 more source

Machine Learning‐Assisted Inverse Design of Soft and Multifunctional Hybrid Liquid Metal Composites

Advanced Functional Materials, EarlyView.
A machine learning framework is presented for inverse design of synthesizable multifunctional composites containing both liquid metal and solid inclusions. By integrating physics‐based modeling, data‐driven prediction, and Bayesian optimization, the approach enables intelligent design of experiments to identify optimal compositions and realize these ...
Lijun Zhou, Yunsik Ohm, Ren‐Mian Chin, Olivia Kerr, Krithika Manohar, Mohammad H. Malakooti   +5 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

Exploring Pb‐Chelation Chemistry in the Crystallization Dynamics of Halide Perovskites

Advanced Functional Materials, EarlyView.
A mechanism of how Pb‐chelation chemistry governs coordination geometry and initial nucleation behavior at the precursor level of halide perovskite, by regulating the deprotonation state of a chelating additive, is elucidated. This allows for innovative reaction‐system design principles that promote coherent growth while suppressing defect formation in
Byeong Jun Kim, Inseo Cho, Jung Geon Son, Yifan Yu, Gunhee Kim, Eunseo Shin, Seyeon Eom, Minsub Um, Subeom Shin, Hyungju Ahn, Dong Suk Kim, Hochan Song, Hyosung Choi, Jonghee Yang   +13 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

Electrode and Microstructure Dependence of Oxygen Diffusion in Ferroelectric Hafnium Zirconium Oxide Thin Films

Advanced Functional Materials, EarlyView.
Significant nanoscale oxygen diffusion coefficient variations are measured in ferroelectric hafnium zirconium oxide films with grain boundaries and electrode interfaces exhibiting values 104 times larger than the grain cores. Overall coefficients are 10X larger for films prepared with metal nitride electrodes compared to refractory metals. New insights
Liron Shvilberg, Thomas W. Pfeifer, Chuanzhen Zhou, Yong Kyu Choi, Duk‐Hyun Choe, Patrick E. Hopkins, Jon F. Ihlefeld   +6 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

Calibrating cardiac electrophysiology models using latent Gaussian processes on atrial manifolds. [PDF]

Sci Rep, 2022
Coveney S, Roney CH, Corrado C, Wilkinson RD, Oakley JE, Niederer SA, Clayton RH.   +6 more
europepmc   +1 more source