Abstract: Bayesian inference provides a methodology for parameter estimation and uncertainty quantification in machine learning and deep learning methods. Variational inference and Markov Chain ...

Version 3.0.0 of this project ends support for Python 2.7, 3.3, and 3.4. We recommend migrating your projects to Python 3.5 or newer as soon as possible. We'll be happy to answer any questions you ...

This repository contains the source code for TensorFlow Privacy, a Python library that includes implementations of TensorFlow optimizers for training machine learning ...

So, you want to learn Python? That’s cool. A lot of people are getting into it these days because it’s used for all sorts of things, from building websites to analyzing data. If you’re looking for a ...

Abstract: Simulation is an excellent tool to study real-life systems with uncertainty. Discrete-event simulation (DES) is a common simulation approach to model time-dependent and complex systems.

With countless applications and a combination of approachability and power, Python is one of the most popular programming languages for beginners and experts alike. We’ve compiled a list of 10 online ...