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This post is a first introduction to MCMC modeling with tfprobability, the R int...
PixelCNN is a deep learning architecture - or bundle of architectures - designed...
Compared to other applications, deep learning models might not seem too likely a...
Deep learning need not be irreconcilable with privacy protection. Federated lear...
A new sparklyr release is now available. This sparklyr 1.2 release features new ...
A new release of pins is available on CRAN today. This release adds support to t...
The term "federated learning" was coined to describe a form of distributed model...
Kullback-Leibler divergence is not just used to train variational autoencoders o...
Broadcasting, as done by Python's scientific computing library NumPy, involves d...
TensorFlow 2.1, released last week, allows for mixed-precision training, making ...
Differential Privacy guarantees that results of a database query are basically i...
TensorFlow Hub is a library for the publication, discovery, and consumption of r...
Continuing our tour of applications of TensorFlow Probability (TFP), after Bayes...
Looking for materials to get started with deep learning from R? This post presen...
Part of the r-tensorflow ecosystem, tfprobability is an R wrapper to TensorFlow ...