How not to get a headache working with diffusion models.

Diffusion models are all the rage these days. They are a new class of generative models, which are capable of generating high-quality images. They have attracted a lot of attention...

Back in 1952 Hodgkin and Huxley found that there are three main types of currents describing the dynamics of a neuron: Sodium (N), Potassium (K), and a leak current, which...

How to sample from a distribution using Langevin Dynamics and why it works.

Generative models rely on the ability to sample from a distribution. When the distribution is known the task of sampling from it is straightforward, for example, sampling from a normal...

Linear Regression (LR) is one of the most fundamental algorithms in machine learning. It is the simplest regression model out there it is very often a fitting solution for a...

The year 2020 was not the greatest for sailors. The pandemic limited the available options for voyages or even to gather a crew. I am a huge sailing enthusiast and...

Any machine learning student will learn about loss functions sooner rather than later. They are a fundamental element of learning and optimisation, therefore understanding is necessary for mastering machine learning....

Gradient descent is probably one of the most widely used algorithm in Machine Learning and Deep Learning. At the same time, it is one of the easiest to understand. In...