Results 121 to 130 of about 4,778,088 (249)
Inference for extremal conditional quantile models, with an application to market and birthweight risks [PDF]
Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to
Victor Chernozhukov +1 more
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, 2003 The subgradient method of N.Z. Shor and B.T. Polyak is used for solving limit extremal problems. Under assumptions involving continuous convergence of functions strong and weak convergence of the aaproximations of the solution is ...
Ivanov, Vsevolod
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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
wiley +1 more source
Advanced Materials, EarlyView.The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj +8 more
wiley +1 more source
Higher level extremal problems
, 1996 Ahlswede R, Cai N, Zhang Z. Higher level extremal problems. Comb. Inf. & Syst. Sc.
Cai, Ning, Zhang, Zhen, Ahlswede, Rudolf
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Problem on extremal decomposition of the complex plane
Analele Stiintifice ale Universitatii Ovidius Constanta: Seria Matematica, 2019 In geometric function theory of a complex variable problems on extremal decomposition with free poles on the unit circle are well known.
Denega Iryna, Zabolotnii Yaroslav
doaj +1 more source
Organic Materials of Tomorrow: Horizons of Artificial Intelligence
Advanced Materials, EarlyView.This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena +3 more
wiley +1 more source
Extremal Problems in Spaces of Analytic Functions
, 2014 Extremal problems have long played an important role in complex analysis. For example, the proof of the Riemann mapping theorem involves an extremal problem, and the famous Bieberbach conjecture (proved by de Branges) is about an extremal problem. I will
Ferguson, Timothy
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Phase Engineering of Nanomaterials (PEN): Evolution, Current Challenges, and Future Opportunities
Advanced Materials, EarlyView.This review summarizes the synthesis, phase transition, advanced characterization spanning ex situ to in situ and operando techniques, and diverse applications of phase engineering of nanomaterials (PEN). It further outlines key challenges and future opportunities, such as phase stability, architecture control, and artificial intelligence (AI)‐driven ...
Ye Chen +7 more
wiley +1 more source
Extremal Events in a Bank Operational Losses [PDF]
Operational losses are true dangers for banks since their maximal values to signal default are difficult to predict. This risky situation is unlike default risk whose maximum values are limited by the amount of credit granted.
Daniel Zajdenweber +2 more
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