Results 81 to 90 of about 898,588 (270)
Deep Learning and Bayesian Methods
EPJ Web of Conferences, 2017 A revolution is underway in which deep neural networks are routinely used to solve diffcult problems such as face recognition and natural language understanding.
Prosper Harrison B.
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Advanced Materials, EarlyView.Metal‐free carbon catalysts enable the sustainable synthesis of hydrogen peroxide via two‐electron oxygen reduction; however, active site complexity continues to hinder reliable interpretation. This review critiques correlation‐based approaches and highlights the importance of orthogonal experimental designs, standardized catalyst passports ...
Dayu Zhu +3 more
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Active Learning‐Guided Accelerated Discovery of Ultra‐Efficient High‐Entropy Thermoelectrics
Advanced Materials, EarlyView.An active learning framework is introduced for the accelerated discovery of high‐entropy chalcogenides with superior thermoelectric performance. Only 80 targeted syntheses, selected from 16206 possible combinations, led to three high‐performance compositions, demonstrating the remarkable efficiency of data‐driven guidance in experimental materials ...
Hanhwi Jang +8 more
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Bayesian methods and decision making in glaucoma
Vision Pan-America, 2013 This article reviews the Bayesian statistical approach to diagnostic test analysis and application in the management of glaucoma patients. The central idea of the Bayesian method is the use of study data to update the state of knowledge about a quantity ...
Niro Kasahara
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Bayesian Methods in Nonlinear Time Series [PDF]
This paper reviews the analysis of the threshold autoregressive, smooth threshold autoregressive, and Markov switching autoregressive models from the Bayesian perspective.
Korenok Oleg
core
Navigating Ternary Doping in Li‐ion Cathodes With Closed‐Loop Multi‐Objective Bayesian Optimization
Advanced Materials, EarlyView.The search for advanced battery materials is pushing us into highly complex composition spaces. Here, a space with about 14 million unique combinations is efficiently explored using high‐throughput experimentation guided by Bayesian optimization with a deep kernel trained on both the Materials Project database and our data.
Nooshin Zeinali Galabi +6 more
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Advanced Materials, EarlyView.This review highlights the role of self‐assembled monolayers (SAMs) in perovskite solar cells, covering molecular engineering, multifunctional interface regulation, machine learning (ML) accelerated discovery, advanced device architectures, and pathways toward scalable fabrication and commercialization for high‐efficiency and stable single‐junction and
Asmat Ullah, Ying Luo, Stefaan De Wolf
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Bayesian statistics and Monte Carlo methods
Journal of Geodetic Science, 2018 The Bayesian approach allows an intuitive way to derive the methods of statistics. Probability is defined as a measure of the plausibility of statements or propositions. Three rules are sufficient to obtain the laws of probability.
Koch K. R.
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Superionic Amorphous Li2ZrCl6 and Li2HfCl6
Advanced Materials, EarlyView.Amorphous Li2HfCl6 and L2ZrCl6 are shown to be promising solid‐state electrolytes with predicted ionic conductivities >20 mS·cm−1. Molecular dynamics simulations with machine‐learning force fields reveal that anion vibrations and flexible MCl6 octahedra soften the Li coordination cage and enhance mobility. Correlation between Li‐ion diffusivity and the
Shukai Yao, De‐en Jiang
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Hydrogel‐Based Functional Materials: Classifications, Properties, and Applications
Advanced Materials Technologies, EarlyView.Conductive hydrogels have emerged as promising materials for smart wearable devices due to their outstanding flexibility, multifunctionality, and biocompatibility. This review systematically summarizes recent progress in their design strategies, focusing on monomer systems and conductive components, and highlights key multifunctional properties such as
Zeyu Zhang, Zao Cheng, Patrizio Raffa
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