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

If a movement is going to thrive, it has to appeal to the young — they'll be the ones to inherit it, after all. Free software is no exception. A bright future for free software depends on young people ...

UPDATE March 8, 2021: This repository is no longer under development. Together with Mike Kestemont and Allen Riddell, I have published a much more comprehensive book about processing humanities data ...

Abstract: Data-driven Quality of Experience (QoE) modeling using Machine Learning (ML) is a key enabler for future communication networks as it allows accelerated and unbiased QoE modeling while ...

These days, the best iPhone apps can be a challenge to find, due to there being almost two million apps available to download in the App Store. You're usually reduced to checking the top charts to see ...

Building on the growing body of research highlighting the capabilities of Large Language Models (LLMs) like Generative Pre-trained Transformers (GPT), this paper presents a structured pipeline for the ...

The Distant Viewing Toolkit is a Python package that facilitates the computational analysis of still and moving images. The most recent version of the package focuses on providing a minimal set of ...

I wore the world's first HDR10 smart glasses TCL's new E Ink tablet beats the Remarkable and Kindle Anker's new charger is one of the most unique I've ever seen Best laptop cooling pads Best flip ...