A new Gaussian process framework learns sparse, ordered dependency graphs from irregular electronic health records while ...
A new convolutional variational deep embedding model learns a generative latent manifold of EEG microstate topographies, ...
The generation of synthetic market data is widely seen as one of the most promising applications of sophisticated artificial intelligence models, such as generative adversarial networks (GANs) and ...
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.
Despite growing interest in the use of complex models, such as machine learning (ML) models, for credit underwriting, ML models are difficult to interpret, and it is possible for them to learn ...
Dr. James McCaffrey of Microsoft Research says the main advantage of using Gaussian naive Bayes classification compared to other techniques like decision trees or neural networks is that you don't ...
Simulated prostate treatment plan in the simple heterogeneous phantom. (Courtesy: J. Appl. Clin. Med. Phys. 10.1002/acm2.12535/CC BY 4.0) A new treatment planning system (TPS) for proton therapy has ...
Swaptions and constant maturity swap spread options are essential to calibrating interest rate models yet remain computationally demanding. Toufik Bellaj, Khalid Bellaj and Hicham Nait Yahia propose a ...
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