Results 61 to 70 of about 11,564,802 (285)

Enhancing Cluster Accuracy in Diabetes Multimorbidity With Dirichlet Process Mixture Models

IEEE Access
Clustering of diabetic multimorbidity data from EHRs is challenging due to patient heterogeneity, high-dimensional variables, sensitivity to parameter settings, and high computational demands, which complicate clustering processes and may result in ...
Francis John Kita, Srinivasa Rao Gaddes, Peter Josephat Kirigiti   +2 more
doaj   +1 more source

Massively Distributed Clustering via Dirichlet Process Mixture [PDF]

, 2021
Dirichlet Process Mixture (DPM) is a model used for multivariate clustering with the advantage of discovering the number of clusters automatically and offering favorable characteristics, but with prohibitive response times, which makes centralized DPM approaches inefficient.
Meguelati, Khadidja, Fontez, Bénédicte, Hilgert, Nadine, Masseglia, Florent, Sanchez, Isabelle   +4 more
openaire   +3 more sources

Charting Endocrine Progenitors Across Species and Organs

Advanced Science, EarlyView.
Endocrine progenitors give rise to the hormone‐producing cells of the pancreas and intestine. Using single‐cell multiomics and proteomics, this study compares these progenitors across species, systems, and organs, mapping the conserved and species‐specific gene regulatory networks that guide their formation.
Changying Jing, Michael Sterr, Özüm Sehnaz Caliskan, Lama Saber, Nicole Katarina Rogers, Samuel Ogden, Kei Kozawa, Christos Karampelias, Jessica Jaki, Aimée Bastidas‐Ponce, Falk Janos Farkas, Oliver Czarnecki, Osvaldo Rodrigues Pereira, Perla Cota, Valerie Vandenbempt, Diego Balboa, Anika Böttcher, Natalie Krahmer, Mohammad Lotfollahi, Julie B. Sneddon, Heiko Lickert, Mostafa Bakhti   +21 more
wiley   +1 more source

Unraveling the Effects of Depolarization in Ultrathin Barium Titanate

Advanced Science, EarlyView.
This article employs synchrotron‐based spectroscopy, time‐resolved electrical measurements, and phase‐field simulations to establish reverse‐domain formation as the mechanism of polarization loss in ultrathin BaTiO3${\rm BaTiO}_3$ films as a critical obstacle to low‐voltage ferroelectric devices.
Thomas Lee, Prabhat Kumar, Christoph Klewe, Pravin Kavle, Padraic Shafer, Zhi (Jackie) Yao, Lane W. Martin   +6 more
wiley   +1 more source

Consensus Clustering for Multi-Source Data Integration via Dirichlet Process Mixture Models

IEEE Access
The integration of multiple heterogeneous data sources for consensus clustering presents substantial methodological challenges, particularly when the true number of clusters is unknown and data sources provide conflicting information.
Nurul Afiqah Burhanuddin
doaj   +1 more source

Variational Low-Rank Matrix Factorization with Multi-Patch Collaborative Learning for Hyperspectral Imagery Mixed Denoising

Remote Sensing, 2021
In this study, multi-patch collaborative learning is introduced into variational low-rank matrix factorization to suppress mixed noise in hyperspectral images (HSIs).
Shuai Liu, Jie Feng, Zhiqiang Tian
doaj   +1 more source

Mixtures of Stick-Breaking Processes [PDF]

, 2008
We consider mixtures of stickbreaking processes as a generalization of the mixture of Dirichlet process model. We provide a sampling algorithm which covers all such models provide specific reasons for using particular choices of prior.
Walker, Stephen G., Kalli, Maria
core  

Determinants of Knowledge and Usage of Generative Artificial Intelligence in Agricultural Extension: Evidence From Tennessee Extension Personnel

Agribusiness, EarlyView.
ABSTRACT This paper examines the determinants of generative AI (GenAI) knowledge and usage among agricultural extension professionals. Drawing on survey data from agricultural extension personnel in Tennessee, we employ regression analyses and latent Dirichlet allocation (LDA) for topic modeling of open‐ended responses to study the knowledge and usage ...
Abdelaziz Lawani, Jason de Koff, James Muriuki, Anna‐Liisa Ihuhwa   +3 more
wiley   +1 more source

Comparative evaluation of alternative Bayesian semi-parametric spatial crash frequency models

Journal of Traffic and Transportation Engineering (English ed. Online)
Albeit with the notable benefits associated with Dirichlet crash frequency models and spatial ones, there is little research dedicated to exploring their combined advantages.
Gurdiljot Singh Gill, Wen Cheng, Mankirat Singh, Yihua Li   +3 more
doaj   +1 more source

A note on posterior sampling from Dirichlet mixture models [PDF]

, 2008
In this note we observe that the recent MCMC methods of Papaspiliopoulos & Roberts (2008) and Walker (2007) for Dirichlet mixture models are intrinsically con- nected and can be naturally combined to yield an algorithm which is better (in terms of ...
Papaspiliopoulos, Omiros
core