Gaussian processes and the Kullback-Leibler divergence have been deeply studied in statistics and machine learning. This paper marries these two concepts and introduce the local Kullback-Leibler divergence to learn about intervals where two Gaussian processes differ the most. We address subtleties entailed in the estimation of local divergences and the corresponding interval of local maximum divergence as well. The estimation performance and the numerical efficiency of the proposed method are showcased via a Monte Carlo simulation study. In a medical research context, we assess the potential of the devised tools in the analysis of electrocardiogram signals.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11604031 | PMC |
| http://dx.doi.org/10.1002/bimj.70018 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Mode-informed complex-valued neural processes for matched field processing.
J Acoust Soc Am
January 2025
School of Information and Electronics, Beijing Institute of Technology, Beijing 100081, People's Republic of China.
A complex-valued neural process method, combined with modal depth functions (MDFs) of the ocean waveguide, is proposed to reconstruct the acoustic field. Neural networks are used to describe complex Gaussian processes, modeling the distribution of the acoustic field at different depths. The network parameters are optimized through a meta-learning strategy, preventing overfitting under small sample conditions (sample size equals the number of array elements) and mitigating the slow reconstruction speed of Gaussian processes (GPs), while denoising and interpolating sparsely distributed acoustic field data, generating dense field data for virtual receiver arrays.
View Article and Find Full Text PDFIn-line prediction of viability and viable cell density through machine learning-based soft sensor modeling and an integrated systems approach: An industrially relevant PAT case study.
Biotechnol Prog
January 2025
Amgen, Cambridge, Massachusetts, USA.
The biopharmaceutical industry is shifting toward employing digital analytical tools for improved understanding of systems biology data and production of quality products. The implementation of these technologies can streamline the manufacturing process by enabling faster responses, reducing manual measurements, and building continuous and automated capabilities. This study discusses the use of soft sensor models for prediction of viability and viable cell density (VCD) in CHO cell culture processes by using in-line optical density and permittivity sensors.
View Article and Find Full Text PDFAssessing time series correlation significance: A parametric approach with application to physiological signals.
Biomed Signal Process Control
August 2024
CNRS-University of Montpellier LIRMM, UMR5506, Interactive Digital Human, Montpellier, France.
Correlation coefficients play a pivotal role in quantifying linear relationships between random variables. Yet, their application to time series data is very challenging due to temporal dependencies. This paper introduces a novel approach to estimate the statistical significance of correlation coefficients in time series data, addressing the limitations of traditional methods based on the concept of effective degrees of freedom (or effective sample size, ESS).
View Article and Find Full Text PDFPhosphoric acid based geopolymer foam-activated carbon composite for methylene blue adsorption: isotherm, kinetics, thermodynamics, and machine learning studies.
RSC Adv
January 2025
National Centre of Excellence in Physical Chemistry, University of Peshawar Peshawar Pakistan.
In this study, a binary composite adsorbent based on activated carbon and phosphoric acid geopolymer foam (ACP) was prepared by combining phosphoric acid geopolymer (PAGP) with activated carbon (AC) and applied for the removal of methylene blue (MB). Activated carbon was thoroughly mixed with a mixture of fly ash and metakaolin in varying ratios, followed by phosphoric acid activation and thermal curing. The ACP adsorbent was characterized using scanning electron microscope (SEM), Fourier transform infrared (FTIR) spectrophotometer, X-ray diffractometer (XRD), surface area analyser (SAP), and thermogravimetric analyser (TGA).
View Article and Find Full Text PDFEffects of soil water on fungal community composition along elevational gradients on the northern slope of the Central Kunlun Mountains.
Front Microbiol
January 2025
Xinjiang Key Laboratory of Desert Plant Roots Ecology and Vegetation Restoration, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China.
Soil fungi are essential to ecosystem processes, yet their elevational distribution patterns and the ecological mechanisms shaping their communities remain poorly understood and actively debated, particularly in arid regions. Here, we investigated the diversity patterns and underlying mechanisms shaping soil fungal communities along an elevational gradient (1,707-3,548 m) on the northern slope of the Central Kunlun Mountains in northwest China. Results indicated that the dominant phyla identified across the seven elevational gradients were and , displaying a unimodal pattern and a U-shaped pattern in relative abundance, respectively.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!