Results 201 to 210 of about 9,300 (265)

An Integrated Gradient Boosting Machine Approach With Fisher's Discriminant Analysis: Empirical Assessment on Five Benchmark Datasets and Simulations

Statistical Analysis and Data Mining: An ASA Data Science Journal, Volume 19, Issue 5, October 2026.
ABSTRACT The aim of this study is to assess the impact of different dimensionality reduction techniques—specifically Principal Component Analysis (PCA) and Fisher's Linear Discriminant Analysis (LDA)—on the classification performance of Gradient Boosting Machines (GBM).
Giulio Enzo Donninelli, Pietro Giorgio Lovaglio   +1 more
wiley   +1 more source

Coupled Bayesian Identification of Residual Stress and Fracture Strength in Thin-Film Fragmentation: A Physics-Informed Neural Network Framework with Synthetic Validation of Interface Adhesion Energy. [PDF]

Materials (Basel)
Li J, Li L, Wang Z, Li C, Wang S, Kang K.   +5 more
europepmc   +1 more source

Automatic GNSS Coordinate Time Series Analysis for Very Large Networks

Earth and Space Science, Volume 13, Issue 10, October 2026.
Abstract We present a new algorithm, AutoCF, for automatically constructing coordinate functions (CFs) for continuously operating GNSS reference stations (CORSs). The iterative algorithm alternates between application of LASSO and Ridge Regression methods, with hyperparameters successively tightened with each iteration to more judiciously scrutinize ...
Richard A. Bennett, Phillip K. McFarland, Amy Whetter, Jordan Krcmaric   +3 more
wiley   +1 more source

Online Bias Estimation for Single-Platform Airborne Radar Using Bias-Subspace Information-Guided MAP-EKF. [PDF]

Sensors (Basel)
Luo J, Guan X, Song C, Zhang H.
europepmc   +1 more source

Neural Surrogate HMC: On Using Neural Likelihoods for Hamiltonian Monte Carlo in Simulation‐Based Inference

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 5, October 2026.
Abstract Bayesian inference methods such as Markov Chain Monte Carlo (MCMC) typically require repeated computations of the likelihood function, but in some scenarios, this is infeasible and alternative methods are needed. Simulation‐based inference methods address this problem by using machine learning to amortize computations.
L. M. Wolniewicz, P. Sadowski, C. Corti
wiley   +1 more source

Defining Optimal Sampling Strategies for Cefepime Model-Informed Precision Dosing. [PDF]

Ther Drug Monit
Valadez A, Smith BJ, Shields RK, Pan S, Weslander E, Galvin SR, Hughes JH, Hughes MA, Sime FB, Roberts JA, Kiel PJ, Neely MN, Scheetz MH, Rhodes NJ.   +13 more
europepmc   +1 more source

MP‐DualNet: A Dual‐Branch Deep Learning Approach for Magnetopause Boundary Detection Using Simulated SXI Images

Space Weather, Volume 24, Issue 10, October 2026.
Abstract The Earth's magnetopause is a key boundary governing solar wind–magnetosphere coupling. The Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) mission will provide global soft X‐ray imaging of the magnetosphere through solar wind charge exchange (SWCX) emission, offering a new opportunity for remote sensing of magnetopause dynamics ...
Cheng Zhong, Zhongwei Yang, Tianran Sun, Chengyan Huang, Jiajia Liu, Jingnan Guo, Yuming Wang, Chi Wang   +7 more
wiley   +1 more source

Cognitive Process Models Reveal Meaningful Brain-Behavior Associations in the Adolescent Brain Cognitive Development Study Stop-signal Task. [PDF]

J Cogn Neurosci
Barrows A, Weigard A, McCabe M, Potter A, Garavan H, Allgaier N.   +5 more
europepmc   +1 more source

Examining the joint impact of missing data mechanisms and item parameter drift on the accuracy of item response theory-based test equating. [PDF]

PLoS One
Bilicioglu Gunes A, Zeybekoglu Yesil S.
europepmc   +1 more source