Results 101 to 110 of about 2,251,103 (302)

Autonomous Multi‐Objective Nanoscale Characterization of Combinatorial (Al, Sc, B)N Films Reveals Composition‐Dependent Ferroelectric Regimes

Advanced Functional Materials, EarlyView.
Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu, Aditya Raghavan, Utkarsh Pratiush, Ian Mercer, Pochun Hsieh, Albert Suceava, Chih‐Yu Lee, Edgar Dimitrov, Mauricio Terrones, Ichiro Takeuchi, Venkatraman Gopalan, Jon‐Paul Maria, Sergei V. Kalinin   +12 more
wiley   +1 more source

A general approach to Bayesian portfolio optimization [PDF]

We develop a general approach to portfolio optimization taking account of estimation risk and stylized facts of empirical finance. This is done within a Bayesian framework.
Bade, Alexander, Jaekel, Uwe, Frahm, Gabriel   +2 more
core  

Beyond Presumptions: Toward Mechanistic Clarity in Metal‐Free Carbon Catalysts for Electrochemical H2O2 Production via Data Science

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, Hsi‐wen Wu, Xiao Wang, Jie Zhang   +3 more
wiley   +1 more source

Energy-aware frugal Bayesian optimization [PDF]

MATEC Web of Conferences
Modern design optimization frameworks aim first and foremost for models with the most accurate predictions without balancing computational overhead.
Plat Gaston, Saves Paul, Bartoli Nathalie, Lefebvre Thierry, Morlier Joseph   +4 more
doaj   +1 more source

Particle filter with swarm move for optimization [PDF]

, 2008
Copyright @ Springer-Verlag Berlin Heidelberg 2008.We propose a novel generalized algorithmic framework to utilize particle filter for optimization incorporated with the swarm move method in particle swarm optimization (PSO).
Yang, S, Ji, Chunlin, Ji, C, Shengxiang Yang, Zhang, Yangyang, Tong, Mengmeng, Tong, M, Mengmeng Tong, Yang, Shengxiang, Zhang, Y, Chunlin Ji, Yangyang Zhang   +11 more
core   +1 more source

Self‐Assembled Monolayers in p–i–n Perovskite Solar Cells: Molecular Design, Interfacial Engineering, and Machine Learning–Accelerated Material Discovery

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
wiley   +1 more source

Bayesian Optimization for Categorical and Mixed Variables Using a Multinomial Logit Surrogate

Algorithms
Bayesian optimization (BO) is a widely used framework for optimizing expensive black-box functions. Most BO methods rely on Gaussian process (GP) surrogates, which perform well in continuous domains but encounter difficulties when decision variables ...
Muhammad Amir Saeed, Antonio Candelieri
doaj   +1 more source

Bayesian optimization with a finite budget: An approximate dynamic programming approach [PDF]

, 2018
We consider the problem of optimizing an expensive objective function when a finite budget of total evaluations is prescribed. In that context, the optimal solution strategy for Bayesian optimization can be formulated as a dynamic programming instance ...
Lam, Remi Roger Alain Paul, Willcox, Karen E, Wolpert, David H.   +2 more
core  

Using stacking to average bayesian predictive distributions (with discussion) [PDF]

, 2018
Bayesian model averaging is flawed in the M-open setting in which the true data-generating process is not one of the candidate models being fit. We take the idea of stacking from the point estimation literature and generalize to the combination of ...
Grunwald, Peter, Castro-Camilo, Daniela, Li, Meng, Shin, Minsuk, Grushka-Cockayne, Yael, Gelman, Andrew, Lichtendahl, Kenneth C., Iacopini, Matteo, Dawid, A. Philip, van Dijk, Herman K., Lichtendahl, Kenneth C, Yao, Yuling, Zhou, Tianjian, Winkler, Robert L, Aastveit, Knut Are, Dawid, A Philip, Yoo, William Weimin, Pericchi, Luis, Clarke, Bertrand, Bakka, Haakon C, Freni-Sterrantino, Anna, Franck, Christopher T., Hoogerheide, Lennart, Tonellato, Stefano, Winkler, Robert L., Simpson, Daniel, Ferreira, Marco A. R., Franco-Villoria, Maria, Belitser, Eduard, Bakka, Haakon C., van Dijk, Herman K, Ferreira, Marco AR, de Heide, Rianne, Nurushev, Nurzhan, Jose, Victor Richmond R., Vehtari, Aki, Clyde, Merlise, McAlinn, Kenichiro, West, Mike, Rue, Havard, Huser, Raphael, Opitz, Thomas, Jose, Victor Richmond R, Franck, Christopher T   +43 more
core   +1 more source

Optimal Control Drives Ultrafast and Energy‐Efficient Magnetization Switching in Van der Waals Magnets

Advanced Materials, EarlyView.
ABSTRACT The accelerating expansion of data‐centric technologies is sharply increasing the energy burden of information storage, placing unprecedented pressure on the efficiency of magnetic switching. Conventional field‐driven reversal, once the foundation of magnetic memory, has become impractical in modern architectures due to its high energy cost ...
Mohammad H. Badarneh, PeiYu Cai, Elton J. G. Santos   +2 more
wiley   +1 more source