Results 171 to 180 of about 34,690 (269)
Transitivity, contextuality and decision making. [PDF]
Sulis WH.
europepmc +1 more source
The Challenge of Handling Structured Missingness in Integrated Data Sources
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 +6 more
wiley +1 more source
Extreme Value Statistics of Community Detection in Complex Networks with Reduced Network Extremal Ensemble Learning (RenEEL). [PDF]
Ghosh T, Zia RKP, Bassler KE.
europepmc +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
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 +1 more
wiley +1 more source
Predictive modeling and ranking of physicochemicals in <i>Aegle marmelos</i> using topological indices and multi-criteria decision-making techniques. [PDF]
Bhandari AN, B J.
europepmc +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Metaconcepts of Rooted Tree Balance. [PDF]
Fischer M, Hamann TN, Wicke K.
europepmc +1 more source
This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source
Delocalisation and Continuity in 2D: Loop O ( 2 ) , Six-Vertex, and Random-Cluster Models. [PDF]
Glazman A, Lammers P.
europepmc +1 more source

