Flow matching (FM) is a recent generative modelling paradigm which has rapidly been gaining popularity in the deep probabilistic ML community. Flow matching combines aspects from Continuous Normalising Flows (CNFs) and Diffusion Models (DMs), alleviating key issues both methods have. In this blogpost we’ll cover the main ideas and unique properties of FM models starting from the basics.
This tutorial introduces the main blocks needed to build a deep learning library in a few lines of Python. You'll learn how to build your (very) light-weight version of PyTorch!
This short tutorial aims at introducing support vector machine (SVM) methods from its mathematical formulation along with an efficient implementation in a few lines of Python! Do play with the full code hosted on my github page. I strongly recommend reading Support Vector Machine Solvers (from L. Bottou & C-J. Lin) for an in-depth cover of the topic, along with the LIBSVM library. The present post naturally follows this introduction on SVMs.
If you are passing by Oxford as a tourist, a visiting student or have already been living there for a while, you cannot miss the enthralling excitement happening around the many bars and pubs scattered in the city. There are especially a significant selection of front and back gardens which offer the perfect place to drink a pint or a glass of Pimm's. I hope you'll love my hand-curated list of the most thrilling beer gardens one can find in The City of Dreaming Spires!