Results 211 to 220 of about 179,516 (314)

The impact of data imputation on air quality prediction problem. [PDF]

PLoS One
Hua V, Nguyen T, Dao MS, Nguyen HD, Nguyen BT.   +4 more
europepmc   +1 more source

KAN-Transformer Fusion with Mixture of Experts for Temporal Imputation of Spatiotemporal Air Pollution Data [PDF]

Jiawen Ding
openalex   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, EarlyView.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Data imputation and domain-adaptive prediction of 1-year postoperative mortality in geriatric hip fracture patients following arthroplasty from multi-center study. [PDF]

Int J Surg
Lu X, Zeng C, Gong Z, Jin R, Zhang Z, Liu K, Hu N, Xiao J, Xiong Y.   +8 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

Traffic data imputation via knowledge graph-enhanced generative adversarial network. [PDF]

PeerJ Comput Sci
Liu Y, Shen G, Liu N, Han X, Xu Z, Zhou J, Kong X.   +6 more
europepmc   +1 more source

Machine Learning‐Enhanced Random Matrix Theory Design for Human Immunodeficiency Virus Vaccine Development

Advanced Intelligent Discovery, EarlyView.
This study integrates random matrix theory (RMT) and principal component analysis (PCA) to improve the identification of correlated regions in HIV protein sequences for vaccine design. PCA validation enhances the reliability of RMT‐derived correlations, particularly in small‐sample, high‐dimensional datasets, enabling more accurate detection of ...
Mariyam Siddiqah, Muhammad Zulqarnain Zeb, Muhammad Husnain Zeb, Babar Shabbir   +3 more
wiley   +1 more source

Missing data imputation using classification and regression trees. [PDF]

PeerJ Comput Sci
Chen CY, Chang YW.
europepmc   +1 more source

MH-GIN: Multi-Scale Heterogeneous Graph-Based Imputation Network for AIS Data [PDF]

Hengyu Liu, Tianyi Li, Yuan He, Kristian Torp, Yushuai Li, Christian S. Jensen   +5 more
openalex   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source