Tag: Bayesian inference

Researchers have introduced a statistical model designed to predict disease from microbiome data pooled across many studies, addressing a persistent ...

The open-source VIPR framework standardizes machine-learning inference for ill-posed inverse problems in reflectometry and beyond through configurable, reproducible workflows.

A perspective article in Frontiers in Computational Neuroscience argues that virtual brain models are already capturing disease mechanisms in patients ...

Researchers developed an ensemble-based Bayesian filtering method that estimates the unmeasurable heat flux between molten steel and a continuous casting ...

Researchers have developed an importance-sampling-based black box variational inference algorithm that reuses earlier simulation evaluations to cut the computational cost ...

A new Bayesian framework called PIML combines machine learning analysis of electrical impedance signals with clinical prior knowledge, improving diagnostic ...

A Bayesian Markov chain Monte Carlo analysis of the Bc meson spectrum across three confining potential models finds stable low-lying ...

A Bayesian data-driven method combining multiple physical constraints improved prediction, uncertainty, and mass balance in synthetic and laboratory groundwater contamination ...

A comparative study of chloroplast genomes from 18 Rhododendron species placed R. ambiguum near R. concinnum but did not resolve ...

A hierarchical multinomial N-mixture model estimated populations of invasive coypus and muskrats remaining after trapping, showing the value of joint ...