JSTOR Daily

Hybridizing Machine Learning Methods and Finite Mixture Models for Estimating Heterogeneous Treatment Effects in Latent Classes

There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum ...
Visual Studio Magazine

Gaussian Mixture Model Data Clustering from Scratch Using C#

Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.
JSTOR Daily

Quasi-Bayes properties of a procedure for sequential learning in mixture models

Bayesian methods are often optimal, yet increasing pressure for fast computations, especially with streaming data, brings renewed interest in faster, possibly suboptimal, solutions. The extent to ...
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 ...
Kaleido Scope

Deep machine-learning speeds assessment of fruit fly heart aging and disease, a model for human disease

Researchers at the University of Alabama at Birmingham now show a way to significantly cut the time needed for that analysis while utilizing more of the heart region, using deep learning and ...
Visual Studio Magazine

Gaussian Mixture Model Data Clustering from Scratch Using C#

Data clustering is the process of grouping data items so that similar items are placed in the same cluster. There are several different clustering techniques, and each technique has many variations.