Results 81 to 90 of about 3,081,373 (191)

Deep Spatially Varying Coefficient Model for Interpolation of Non‐Stationary Meteorological Data

Environmetrics, Volume 37, Issue 6, September 2026.
ABSTRACT In spatial statistics, the spatially varying coefficient model (SVCM) is widely applied in the analysis and interpolation of non‐stationary spatial data. By incorporating spatially varying coefficients, the model can capture spatial heterogeneity and provide an attractive interpretation of response‐covariate associations.
Tong Wu, Nan Chen, Zhi‐Sheng Ye
wiley   +1 more source

Lysosomal Dysfunction Is Associated With Intervertebral Disc Degeneration: Multiomics and Machine Learning Identify Molecular Subtypes and Hub Genes

The Journal of Gene Medicine, Volume 28, Issue 9, September 2026.
Intervertebral disc degeneration (IVDD) is linked to lysosomal dysfunction, impaired autophagic degradation, and cellular senescence. Integrating bulk and single‐cell transcriptomics with machine learning, this study identified two lysosome‐related molecular subtypes and four hub genes: HYAL1, MMD, PLD3, and ANK3.
Yang Yang, Hong Li, Yixuan Ou, Yaping Yu, Kaiqiang Sun, Shixing Chen, Chenglong Ji   +6 more
wiley   +1 more source

An Efficient, Variational Approximation of the Best Fitting Multi-Bernoulli Filter [PDF]

IEEE Transactions on Signal Processing, 2015
Accepted, IEEE Transactions on Signal Processing, http://dx.doi.org/10.1109/TSP.2014 ...
openaire   +5 more sources

A Guide for Exploring Pleiotropic Associations in Genome‐Wide Association Studies Using Summary Statistics

Statistics in Medicine, Volume 45, Issue 20-22, September 2026.
ABSTRACT Genome‐wide association studies (GWAS) have shown that pleiotropy, whereby a single genetic variant or gene influences multiple traits, is common in complex human diseases. Detecting cross‐phenotype associations from GWAS summary statistics remains challenging because of small effect sizes, extensive multiple testing, heterogeneous effects ...
Christina Y. Feng, Pierre‐Emmanuel Sugier, Nan Zou, Benoit Liquet   +3 more
wiley   +1 more source

Innovative Filter for Nonlinear Multitarget Tracking: Improved SCKF-GM-DLPMBM Filter and Its Implementation

IEEE Access
The Poisson multi-Bernoulli mixture (PMBM) filter is capable of estimating the states of multiple targets based on available measurements. To address the limitations of the traditional PMBM filter, which involves the enumeration of assumptions that ...
Yubin Zhou, Bo Li, Jinyu Zhang, Zhikang Li   +3 more
doaj   +1 more source

Cross‐continental zero‐shot anuran call classification with CLAP and denoising‐based synthetic embedding generation

Methods in Ecology and Evolution, Volume 17, Issue 9, Page 2701-2712, September 2026.
Abstract Using machine learning models to classify bioacoustic signals of animal species is increasingly important for conservation monitoring because manual expert labelling is time‐consuming and tedious. Monitoring endangered species is particularly challenging because these species are rare, making it difficult to collect the large, representative ...
Ysobel Sims, Oliver Kelly, Andrea S. Griffin, Eric Johns, Alexandre Mendes, Alex Callen, Matt W. Hayward, Stephan Chalup   +7 more
wiley   +1 more source

Robust Poisson Multi-Bernoulli Mixture Filter With Inaccurate Process and Measurement Noise Covariances

IEEE Access, 2020
This paper proposes a robust Poisson multi-Bernoulli mixture (PMBM) filter with inaccurate process and measurement noise covariances. A derivation of the robust PMBM filter is provided for jointly estimating the kinematic state, the predicted state ...
Wenjuan Li, Hong Gu, Weimin Su
doaj   +1 more source

Eco‐evolutionary context modifies a destructive plant invader's response to climate

New Phytologist, Volume 251, Issue 5, Page 2980-2994, September 2026.
Abiotic environment–fitness relationships can be shaped by evolutionary, ecological, and eco‐evolutionary contexts. Summary Understanding the relationship between climate and fitness will be important when predicting how plant populations respond to climate change. We conducted a replicated common garden experiment (4 sites × 2 yr) with 96 genotypes (n 
Megan L. Vahsen, Justin J. Van Ee, Diana Gamba, Toby M. Maxwell, Nikki Pirtel, Seth J. Romero, David T. Barnett, Owen Baughman, David J. Ensing, Richard Gill, Martin C. Holdrege, Ruth A. Hufbauer, Rebecca Hufft, Chandra E. Moffat, Jacqueline Ott, Lysandra Pyle, Corinne Schroeder, Eugene W. Schupp, Robert K. Shriver, Michael Stemkovski, Amy J. Symstad, Alexandra K. Urza, Dana M. Blumenthal, Cynthia Brown, Matthew J. Germino, Mevin B. Hooten, Jesse R. Lasky, Elizabeth A. Leger, Lauren M. Porensky, Peter B. Adler   +29 more
wiley   +1 more source

An Improved Measurement-Oriented Marginal Multi-Bernoulli/Poisson Filter [PDF]

Radioengineering, 2019
The measurement-oriented marginal multi-Ber-noulli/Poisson (MOMB/P) filter is an attractive approach for multi-target tracking. However, the effect of measure¬ment on predicted target states may be weakened when the hypothesized tracks are separated ...
Z. Z. Su, H. B. Ji, Y. Q. Zhang
doaj  

Adaptive cardinality balanced multi-target multi-Bernoulli filter based on cubature Kalman

The Journal of Engineering, 2019
The sequential Monte Carlo cardinality balanced multi-Bernoulli (SMC-CBMeMBer) filter provides a good framework to cope with the multi-target tracking problem.
Haihuan Wang, Xiaoyong Lyu, Long Ma
doaj   +1 more source