The Mining Journal

The case for Bayesian Learning in mining

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 ...
Nature

Bayesian deep-learning structured illumination microscopy enables reliable super-resolution imaging with uncertainty quantification

The objective of optical super-resolution imaging is to acquire reliable sub-diffraction information on bioprocesses to facilitate scientific discovery. Structured illumination microscopy (SIM) is ...
Nature

Knowledge graph-aided Bayesian active learning for top-K genetic interaction discovery

In silico methods for predicting the effects of multi-gene perturbations hold great promise for advancing functional genomics, computational drug discovery, and disease modeling. However, the ...
Phys.org

Gaussian processes provide a new path toward quantum machine learning

Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...