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

We describe OHBA Software Library for the analysis of electrophysiology data (osl-ephys). This toolbox builds on top of the widely used MNE-Python package and provides unique analysis tools for ...

The bleeding edge: In-memory processing is a fascinating concept for a new computer architecture that can compute operations within the system's memory. While hardware accommodating this type of ...

Hi,I'm David. Programming is my passion, and I hope that rio will make coding easier and more fun. Hi,I'm David. Programming is my passion, and I hope that rio will make coding easier and more fun. Hi ...

This repository contains a collection of Python scripts and Jupyter notebooks for practicing numerical methods commonly used in scientific computing and engineering applications. The exercises cover a ...

Private methods are often used as an implementation detail and are not meant to be accessed directly by the users of a class. The name mangling mechanism in Python makes it difficult to call private ...