Magnus Ross

My friends and I were discussing England’s world cup fortunes at lunch the other day, and there was a strong feeling that our boys would have no chance against France, should that end up being the final.

This is nothing to be proud of, but I have never really studied optimisation in depth.

Or, understanding the Cradle-1 pipeline.

Recently I’ve been thinking a bit about foundation models for time series, and I can’t work out how to feel about them.

The Mind is a collaborative card game that is designed to be fun to play with your friends.

It’s good to read and I like doing it.

Evaluating LLMs is hard.

The Cape Wrath Trail is known, in a somewhat tongue-in-cheek way, as the UK’s hardest trail.

Machine learning for health (ML4H) has a problem with deployment in the clinic.

This is a guide that details how to use the Routegadget website to practice route selection for a mountain marathon.

Unless you’ve been under a rock the past few weeks, you’ve probably heard about Elon Musk’s gaggle of DOGE lads who have been let loose inside the US Treasury payments system.

Benchmark tasks are a cornerstone of ML research, and a large proportion new research in pretty much every subfield follows the following template: Introduce new layer, architecture, optimiser, inference scheme… Run the model on a set of benchmark tasks M…

The EM algorithm for me is one of those things that I feel I should know back to front, since it’s a pretty foundational algorithm in probabilistic ML.

This is a nice problem from the book “Cut the knot”, which is a compilation of probability riddles and brain teasers.

This problem from the GPML book relates to the effect of the choice of measure when using Mercer’s theorem to compute kernel eigenfunctions on the resulting norm in the RKHS induced by that kernel.

It is only the third week and I have already failed to manage my goal of posting one solution per week, not a good sign for the future… In my defense, I was busy last week attending the Probabilistic Numerics Spring School, at which I learned lots about p…

Problem Note: I was brushing up on my SVD using the brilliant “Mathematics for Machine Learning” book, but the exercises listed in the book for SVD were a bit basic, so I decided to try use ChatGPT to generate a question.

Problem Take an objective function f(x) f(x) f(x) with GP prior and i.i.d.

I spent the summer of 2022 visiting Markus Heinonen at Aalto University in Finland.

Update: This paper was published at NeurIPS 2021 check out the final version or my presentation.

There are many interesting things that can be learned about probabilistic modelling from the world of trading and finance, where, perhaps due to the direct connection to very large sums of money, attitudes to problems are generally very different to those…

Near the end of last year I had the privilege of being invited at the 3rd Sheffield Workshop on Structural Dynamics.

There are a lot of podcasts out there, and this includes loads that are related to machine learning in some way.

(Note: This series of posts is closely related to and inspired by this paper from Miles Cranmer, Sam Greydanus, Stephan Hoyer and others.