Bayesian Learning is becoming more feasible and attracting greater interest in mining. But adopting it also comes with some challenges. For one thing, this is a highly specialised branch of statistics ...

The goal of the consortium is to develop innovative quantitative methods to improve the characterization of subsurface reservoirs for hydrocarbon exploration and carbon dioxide sequestration and ...

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 ...

MIT’s scientists claim they can teach a new concept to a computer using a single example rather than thousands. if confirmed, this significantly reduced the requirements needed for machine learning.

No matter what kind of traditional HPC simulation and modeling system you have, no matter what kind of fancy new machine learning AI system you have, IBM has an appliance that it wants to sell you to ...

M. Liu, J. Narciso, D. Grana, E. Van De Vijver, and L. Azevedo, 2023, Frequency-domain electromagnetic induction for the prediction of electrical conductivity and magnetic susceptibility using ...

This course offers a rigorous yet practical exploration of Bayesian reasoning for data-driven inference and decision-making. Students will gain a deep understanding of probabilistic modeling, and ...

Bayesian learning claims that the strength of the price impact of unanticipated information depends on the relative precision of traders' prior and posterior beliefs. In this paper, we test for this ...