Abstract: Deep Gaussian process (DGP) models offer a powerful nonparametric approach for Bayesian inference, but exact inference is typically intractable, motivating the use of various approximations.
Kentaro Matsuura (2023). Bayesian Statistical Modeling with Stan, R, and Python. Singapore: Springer. URL: https://link.springer.com/book/10.1007/978-981-19-4755-1 ...
Abstract: Federated learning (FL) is an approach to training machine learning models that takes advantage of multiple distributed datasets while maintaining data privacy and reducing communication ...
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