Results 131 to 140 of about 471,788 (278)

Bayesian learning from multi-way EEG feedback for robot navigation and target identification. [PDF]

Sci Rep, 2023
Wirth C, Toth J, Arvaneh M.
europepmc   +1 more source

Inversion of the Impedance Response Towards Physical Parameter Extraction Using Interpretable Machine Learning

Advanced Energy Materials, EarlyView.
ABSTRACT Interpreting the impedance response of perovskite solar cells (PSCs) is challenging due to the complex coupling of ionic and electronic motion. While drift‐diffusion (DD) modelling is a reliable method, its mathematical complexity makes directly extracting physical parameters from experimental data infeasible.
Mahmoud Nabil, Isel Grau, Ricardo Grau‐Crespo, Said Hamad, Juan A. Anta   +4 more
wiley   +1 more source

Integration of Bayesian Methods in Machine Learning: A Theoretical and Empirical Review

INSERT
Abstrak Studi ini merupakan sebuah tinjauan literatur sistematis yang mendalami integrasi metode Bayesian dalam pembelajaran mesin. Metode Bayesian telah terbukti memberikan keuntungan signifikan dalam menangani ketidakpastian dan variabilitas data ...
Syaharuddin Syaharuddin
doaj   +1 more source

BAYESIAN LEARNING OF COVID-19 VACCINE SAFETY WHILE INCORPORATING ADVERSE EVENTS ONTOLOGY. [PDF]

Ann Appl Stat, 2023
Zhao B, Zhong Y, Kang J, Zhao L.
europepmc   +1 more source

Assessing Mesoscale Heterogeneities in Hard Carbon Electrodes Through Deep Learning‐Assisted FIB‐SEM Characterization, Manufacturing and Electrochemical Modeling

Advanced Energy Materials, EarlyView.
A combination of discrete and finite element method models for the current collector deformation and electrochemical performance analysis, respectively. The models are calibrated and validated with electrochemical and imaging data of hard carbon electrodes. These electrodes were manufactured with different parameters (slurry solid contents of 35 and 40
Soorya Saravanan, Imelda Cardenas‐Sierra, Pei Sun, Hari Raj, Daniele Duranti, Mahnoor Nafees, Edoardo Rossi, Marco Sebastiani, Paul Vigneaux, Martin Petit, Maxime Moreaud, Francisco Fernandez, Alejandro A. Franco   +12 more
wiley   +1 more source

Comparative evaluation of score criteria for dynamic Bayesian Network structure learning.

PLoS ONE
Dynamic Bayesian Networks (DBNs) are probabilistic models with a directional structure employed to model temporal processes. Three approaches to DBN structure learning are constraint-based, score-based, and hybrid.
Aslı Yaman, Mehmet Ali Cengiz
doaj   +1 more source

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Evaluating Machine Learning Approaches in Structural Equation Modelling to Improve Predictive Accuracy in Marketing Research

Indonesian Journal of Business and Entrepreneurship
Background: This study aimed to fill a critical research gap by comparing traditional Structural Equation Modelling (SEM) with hybrid Bayesian-Machine Learning (ML) models in marketing research, focusing on the limited exploration of these advanced ...
Chacha Magasi
doaj   +1 more source

Cramér-Rao Bounds for DoA Estimation of Sparse Bayesian Learning with the Laplace Prior. [PDF]

Sensors (Basel), 2022
Bai H, Duarte MF, Janaswamy R.
europepmc   +1 more source

Disorder‐Driven Fast Na+ Transport: From Crystalline to Amorphous Networks in the Mixed‐Anion NaTaOxCl6−2x Oxychlorides

Advanced Energy Materials, EarlyView.
Oxygen substitution in NaTaOxCl6‐2x drives structural evolution from isolated [TaCl6]– octahedra, through oxygen‐bridged [Ta2OCl10]2– dimers, toward extended trans‐[TaO2Cl4]3– chain‐like arrangements. At intermediate compositions, zero‐dimensional corner‐sharing motifs are proposed to create a flexible, disordered framework that peaks ionic ...
Justin Leifeld, Abigail C. Parsons, Alexandra Morscher, Xabier Martinez de Irujo‐Labalde, Marvin A. Kraft, Oskar G. Soulas, Bibek Samanta, Wiebke Zielasko, Neelam Yadav, Kyra Strotmann, Niina Jalarvo, Bruno V. M. Rodrigues, Adam Slabon, Philipp Adelhelm, Michael Ryan Hansen, David O. Scanlon, Wolfgang G. Zeier, Alexander G. Squires   +17 more
wiley   +1 more source