Results 51 to 60 of about 68,993 (274)
Bayesian spatial SEM for lichen biodiversity
Tonio Di Battista +3 more
openalex +4 more sources
Bayesian hierarchical clustering for studying cancer gene expression data with unknown statistics [PDF]
Clustering analysis is an important tool in studying gene expression data. The Bayesian hierarchical clustering (BHC) algorithm can automatically infer the number of clusters and uses Bayesian model selection to improve clustering quality. In this paper,
A Su +39 more
core +4 more sources
Detecting the Unexpected via Image Resynthesis
Classical semantic segmentation methods, including the recent deep learning ones, assume that all classes observed at test time have been seen during training.
Fua, Pascal +3 more
core +1 more source
A practical degradation based method to predict long-term moisture incursion and colour change in high power LEDs [PDF]
The effect of relative humidity on LEDs and how the moisture incursion is associated to the color shift is studied. This paper proposes a different approach to describe the lumen degradation of LEDs due to the long-term effects of humidity.
Law, Thong Kok, Lim, Fannon
core +1 more source
This paper proposes a novel approach that integrates the capability of empirical validation of structural equation modelling (SEM) and the prediction ability of Bayesian networks (BN).
Wipulanusat Warit +4 more
doaj +1 more source
Background: This study aimed to fill a critical research gap by comparing traditional Structural Equation Modelling (SEM) with hybrid Bayesian-Machine Learning (ML) models in marketing research, focusing on the limited exploration of these advanced ...
Chacha Magasi
doaj +1 more source
Hippocampus-dependent emergence of spatial sequence coding in retrosplenial cortex. [PDF]
Retrosplenial cortex (RSC) is involved in visuospatial integration and spatial learning, and RSC neurons exhibit discrete, place cell-like sequential activity that resembles the population code of space in hippocampus.
Bonin, Vincent +5 more
core +2 more sources
Bayesian comparison of latent variable models: Conditional vs marginal likelihoods
Typical Bayesian methods for models with latent variables (or random effects) involve directly sampling the latent variables along with the model parameters.
Furr, D. +2 more
core +1 more source
Causal relationships between milk quality and coagulation properties in Italian Holstein-Friesian dairy cattle [PDF]
Background: Recently, selection for milk technological traits was initiated in the Italian dairy cattle industry based on direct measures of milk coagulation properties (MCP) such as rennet coagulation time (RCT) and curd firmness 30 min after rennet ...
Cassandro, Martino +3 more
core +4 more sources
Bayesian evaluation of informative hypotheses in SEM using Mplus: A black bear story
Half in jest we use a story about a black bear to illustrate that there are somediscrepancies between the formal use of the p-value and the way it is often usedin practice. We argue that more can be learned from data by evaluatinginformative hypotheses, than by testing the traditional null hypothesis.
Van de Schoot, Rens +2 more
openaire +5 more sources

