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

Google's TorchTPU aims to enhance TPU compatibility with PyTorch Google seeks to help AI developers reduce reliance on Nvidia's CUDA ecosystem TorchTPU initiative is part of Google's plan to attract ...

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Git isn’t hard to learn. Moreover, with a Git GUI such as Atlassian’s Sourcetree, and a SaaS code repository such as Bitbucket, mastery of the industry’s most powerful version control tools is within ...

Robbie has been an avid gamer for well over 20 years. During that time, he's watched countless franchises rise and fall. He's a big RPG fan but dabbles in a little bit of everything. Writing about ...

Operator learning is a transformative approach in scientific computing. It focuses on developing models that map functions to other functions, an essential aspect of solving partial differential ...

Callum is a seasoned gaming managing editor for a number of publications and a gamer who will always try to shine a spotlight on indie games before giving AAA titles the time of day. He loves nothing ...

AI tools are the latest craze to impact the tech industry — and by extension, the rest of the world. For years now, bosses everywhere are trying to boost profits by replacing workers with AI, and ...

I want to land this before PyTorch 2.4 (so we can link to these in PyTorch's nightly documentation) and then have a follow-up PR for 2.4 that actually runs the scripts (so that they can generate ...