Results 141 to 150 of about 136,829,320 (227)
Maximum a posteriori density estimation and the sparse grid combination technique
We study a novel method for maximum a posteriori (map) estimation of the probability density function of an arbitrary, independent and identically distributed d-dimensional data set.
Hegland, Markus, Wong, Matthias
core
Estimation of Total Sleep Time From Respiratory Event Intervals in Sleep Disordered Breathing
ABSTRACT The correct identification of respiratory events and estimation of total sleep time (TST), done in a sleep clinic with polysomnography (PSG), are central elements in the diagnostic process of sleep‐disordered breathing and in the quantification of its severity with the apnoea‐hypopnea index (AHI). However, total sleep time may not be available
Luca Cerina +4 more
wiley +1 more source
ABSTRACT We extend the notion of forward performance criteria to settings with random endowment in incomplete markets. Building on these results, we introduce and develop the novel concept of forward optimized certainty equivalent (forward OCE), which offers a genuinely dynamic valuation mechanism that accommodates progressively adaptive market model ...
Gechun Liang +2 more
wiley +1 more source
ABSTRACT This study develops and validates a scenario‐based assessment for global citizenship within mathematics contexts. It addresses the need for students to engage thoughtfully with global challenges by linking civic education and mathematics. The assessment tool captures competencies essential for global citizenship, including presenting opinions ...
Haemee Rim, Sun Hee Kim, Jihyun Hwang
wiley +1 more source
Data‐Driven Spectral Prediction for Accelerating Large‐Scale Electronic Structure Calculations
ABSTRACT Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling, solving the associated large, sparse generalized eigenproblems remains a critical computational bottleneck on exascale architectures.
Abhiram Badrinarayanan +6 more
wiley +1 more source
Sparsity‐Driven Source Localization in Tomographic Sensing Applications
ABSTRACT Hyperspectral standoff detection systems such as Focal Plane Array (FPA) Fourier Transform Infrared (FTIR) spectrometers provide high spatial resolution in detecting airborne chemical contaminants that are invisible to the human eye but potentially hazardous. When two such systems are operated simultaneously with a suitable opening angle, they
Marco Mattuschka +5 more
wiley +1 more source
Population pharmacokinetic/pharmacodynamic mixture models via maximum a posteriori estimation
Pharmacokinetic/pharmacodynamic phenotypes are identified using nonlinear random effect models with finite mixture structures. A maximum a posteriori probability estimation approach is presented using an EM algorithm with importance sampling.
Schumitzky, Alan +2 more
core
Probing and Graph Coloring Techniques for Trace Estimation in Lattice QCD
ABSTRACT The computation of Tr[D−1]$\mathrm{Tr}[D^{-1}]$, where D$D$ is the Wilson–Dirac matrix of Lattice QCD, is a fundamental and computationally demanding task with applications to disconnected hadronic correlation functions. Since D−1$D^{-1}$ is a dense matrix of prohibitive size, its trace cannot be computed exactly, and one must resort to ...
Mario Papace +5 more
wiley +1 more source
ABSTRACT Regenerative medicine is a promising approach for the treatment of meniscus injuries. In silico experiments provide a valuable framework for optimizing such therapies by improving the understanding of both environmental effects on cell behavior and the interaction between cells and nonwoven scaffolds, which act as porous media supporting cell ...
Ahmad Hussein +3 more
wiley +1 more source
DQN‐Guided Subset‐Induced OCSVM Kernel Approximation for Imbalanced Anomaly Detection
Anomaly detection under limited normal data remains a fundamental challenge due to severe class imbalance and scarcity of anomalies. We propose a novel framework that reformulates support vector selection in One‐Class SVM as a sequential decision‐making problem.
Wenqian Yu, Jiaying Wu, Jinglu Hu
wiley +1 more source

