Results 21 to 30 of about 257 (99)

Lost in Translation: Harmonizing Terminology and Defining Mathematical Tools for Panel Optimization

open access: yesCytometry Part A, Volume 107, Issue 12, Page 793-816, December 2025.
ABSTRACT Spectral flow cytometry has evolved from a contentious idea into a mainstay of high‐parameter single‐cell analysis, yet its vocabulary (and the statistical reasoning behind it) remains a patchwork of overlapping, sometimes contradictory terms.
Bartek Rajwa, Mario Roederer
wiley   +1 more source

Hidden Feature Extraction Based on Mask R‐CNN and Transfer Learning and Its Application in Medical Diagnosis

open access: yesEngineering Reports, Volume 7, Issue 12, December 2025.
The figure systematically presents a framework for cross‐domain medical image analysis. The source domain and target domain images are extracted from the backbone network with shared weights. At this stage, GRL promotes the alignment of feature distribution through an adversarial mechanism.
Xiangqiang Yang   +4 more
wiley   +1 more source

Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions

open access: yesInternational Statistical Review, Volume 93, Issue 3, Page 385-424, December 2025.
Summary In recent years, reinforcement learning (RL) has acquired a prominent position in health‐related sequential decision‐making problems, gaining traction as a valuable tool for delivering adaptive interventions (AIs). However, in part due to a poor synergy between the methodological and the applied communities, its real‐life application is still ...
Nina Deliu   +2 more
wiley   +1 more source

Inhomogeneous broadening in the time domain

open access: yesNanophotonics, Volume 14, Issue 23, Page 4177-4196, 02 November 2025.
Abstract Forty‐five years after the initial attempts – first by Efimov–Khitrov in 1979, then by Brendel–Bormann in 1992 – we present a comprehensive, causal, and physically consistent framework for modeling the dielectric function with inhomogeneous (non‐Lorentzian) broadening, where scattering becomes frequency‐ or time‐dependent.
Ludmila J. Prokopeva   +1 more
wiley   +1 more source

Machine‐learning‐assisted photonic device development: a multiscale approach from theory to characterization

open access: yesNanophotonics, Volume 14, Issue 23, Page 3761-3793, 02 November 2025.
Abstract Photonic device development (PDD) has achieved remarkable success in designing and implementing new devices for controlling light across various wavelengths, scales, and applications, including telecommunications, imaging, sensing, and quantum information processing.
Yuheng Chen   +18 more
wiley   +1 more source

Exploiting Multi‐Objective Reinforcement Learning and Explainable Artificial Intelligence to Navigate Robust Regional Water Supply Investment Pathways

open access: yesWater Resources Research, Volume 61, Issue 11, November 2025.
Abstract Urban water utilities are adopting more advanced dynamic and adaptive infrastructure investment frameworks in the face of hydrologic extremes, accelerating demand, and financial constraints. Evolutionary multi‐objective reinforcement learning has enhanced the identification of high‐performing infrastructure investment pathways that balance ...
Lillian Bei Jia Lau   +2 more
wiley   +1 more source

Stability of Interdiction Strategies in Quickest Flow Networks

open access: yesNetworks, Volume 86, Issue 3, Page 263-281, October 2025.
ABSTRACT Many, if not all, societies have experienced natural disasters, public protests, traffic congestion, and the smuggling of dangerous goods, among other similar events. Such decision‐making and managerial problems can be studied using a game‐theoretic approach on specific networks.
Shahram Morowati‐Shalilvand   +2 more
wiley   +1 more source

Halfspace Depth

open access: yesWIREs Computational Statistics, Volume 17, Issue 3, September 2025.
The halfspace depth generalizes quantiles to multivariate data. This is a bagplot—a depth‐based analog of a boxplot. It succinctly captures the geometry of the bivariate dataset (blue/red points) and identifies the four red points in the top left corner as deviating from the general pattern of the data.
Stanislav Nagy
wiley   +1 more source

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