Results 171 to 180 of about 33,950 (290)

Feature Selection for Machine Learning‐Driven Accelerated Discovery and Optimization in Emerging Photovoltaics: A Review

Advanced Intelligent Discovery, EarlyView.
Feature selection combined with machine learning and high‐throughput experimentation enables efficient handling of high‐dimensional datasets in emerging photovoltaics. This approach accelerates material discovery, improves process optimization, and strengthens stability prediction, while overcoming challenges in data quality and model scalability to ...
Jiyun Zhang, Jiayi Tan, Qizhen Song, Tian Du, Jens Hauch, Christoph J. Brabec   +5 more
wiley   +1 more source

Robust learning for ridge-penalized quasi-GLMs under non-identical distributions. [PDF]

Sci Rep
Zhang H, Tian W, Yao Q, Wang P, Zhang B.
europepmc   +1 more source

Interpretable Machine Learning for Solvent‐Dependent Carrier Mobility in Solution‐Processed Organic Thin Films

Advanced Intelligent Discovery, EarlyView.
This work establishes a correlation between solvent properties and the charge transport performance of solution‐processed organic thin films through interpretable machine learning. Strong dispersion interactions (δD), moderate hydrogen bonding (δH), closely matching and compatible with the solute (quadruple thiophene), and a small molar volume (MolVol)
Tianhao Tan, Lian Duan, Dong Wang
wiley   +1 more source

New robust two-parameter estimator for overcoming outliers and multicollinearity in Poisson regression model. [PDF]

Sci Rep
Mohammad HH, Hammad AT, El-Helbawy AA, Kalantan ZI, Habineza A, Hussam E, Gemeay AM.   +6 more
europepmc   +1 more source

The Challenge of Handling Structured Missingness in Integrated Data Sources

Advanced Intelligent Discovery, EarlyView.
As data integration becomes ever more prevalent, a new research question that emerges is how to handle missing values that will inevitably arise in these large‐scale integrated databases? This missingness can be described as structured missingness, encompassing scenarios involving multivariate missingness mechanisms and deterministic, nonrandom ...
James Jackson, Marius Hofert, Eleni‐Rosalina Andrinopoulou, Niels Hagenbuch, Sarah McGough, Chris Harbron, Robin Mitra   +6 more
wiley   +1 more source

Robust estimation methods for addressing multicollinearity and outliers in beta regression models. [PDF]

Sci Rep
Olaluwoye OT, Lukman AF, Alrasheedi MA, Nzomo WN, Farghali RA.   +4 more
europepmc   +1 more source

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Smooth and shape-constrained quantile distributed lag models. [PDF]

Biometrics
Jin Y, Molstad AJ, Wilson A, Antonelli J.   +3 more
europepmc   +1 more source

Ridge Estimation in Functional Measurement Error Models

, 2001
We propose a ridge estimator as an alternative estimator in the presence of collinearity among the elements of unobservable values in functional measurement error models. Modifications of the estimator are also considered and properties derived which are analogous to those known in ordinary linear models Our simulation results show that the modified ...
openaire   +2 more sources

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley   +1 more source