Nature

Bayesian Inference in Inverse Problems articles from across Nature Portfolio

This Primer examines Skilling’s nested sampling algorithm for Bayesian inference and, more broadly, multidimensional integration. The principles of nested sampling are summarize ...
Phys.org

Inference of Bayesian networks made fast and easy using an extended depth-first search algorithm

A Bayesian network is a directed acyclic graph (DAG) or a probabilistic graphical model used by statisticians. Vertices of this model represent different variables. Any connections between variables ...
Jackson School of Geosciences

Researchers Map Aquifer From the Surface Using Remote Sensing and Statistical Models

A conceptual figure from the study showing how researchers used InSAR deformation data to create a permeability map of ...

Researchers advance aquifer mapping using remote sensing and statistical models to improve groundwater management

Groundwater in many areas of the U.S. and across the globe is being depleted as pumping for drinking water and agriculture ...
Diginomica

Can Bayesian Networks provide answers when Machine Learning comes up short? It's a question of probabilities

Machine Learning gets all the marketing hype, but are we overlooking Bayesian Networks? Here's a deeper look at why "Bayes Nets" are underrated - especially when it comes to addressing probability and ...
lse

Bayesian Inference

This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Economics and Data Science, BSc in Mathematics with Data Science ...