New preprint with V. Karagulyan & M. Kasprzak:
arxiv.org/pdf/2610.20007
We estimate the pseudo-spectral gap of (continuous state-space) Markov chains from a single trajectory. Plugging the estimate into Paulin's version of Bernstein inequality leads to empirical deviation bounds for Markov chains!
A group of 25 Fields Medalists, including myself, have made a joint declaration on Math and AI: mathandai.org . We welcome additional signatories. See also this article in the Economist announcing the declaration: www.economist.com/science-and-...
Just realised I feel about cars like half of you feel about LLMs. βOh but you canβt deny itβs convenientβ I donβt deny itβs convenient, I attest that it sucks to live in the world it created
I was reading today about the Borell-TIS inequality, which is named after Christer Borell, and then three people who had the bad idea of not writing a single author paper.
en.wikipedia.org/wiki/Borell%...
Wow, I love this short piece about writing and revision, comparing students to experts:
psychology.yale.edu/sites/defaul...
Good writing is good thinking. AI might assist but can't do that for me. I'm writing for a deadline tonight, and it's wonderful I get to write, and think, for work.
Anyone know of any papers that directly critique Markov chain Monte Carlo methods for being unreliable (and not just slow/slower than a competing method)? Papers in stats or applied fields welcome, and the critiques don't have to be well-formed or even correct.
Oh I'm actually looking for/collating examples of people (papers) actively shunning MCMC for being unreliable or non-reproducible. Would you happen to know of specific references where this was argued?
Unfortunately these characters are extremely messed up in this one. They were birthed in a nightmare I had.
I don't know if I'm the one playing God with my characters, or if they're the ones playing God with me.
New version available at the same address! We bit the bullet and extended the work to consider arbitrary numbers of blocks, discrete spaces, parallel/systematic/random scan CAVI within a unified framework.
Applications now include statistical physics models and others!
arxiv.org/abs/2605.30253
With friends at the University of Warwick (in particular, Rocco Caprio and @adriencorenflos.bsky.social), we've recently arXived some work (arxiv.org/abs/2605.30253) on a method for approximate inference known as "Coordinate Ascent Variational Inference", or "CAVI" for short. Let me explain:
Our paper (with Alain Durmus, Samuel Gruffaz, Miika Kailas and Eero Saksman) on the ergodicity of dynamic path length HMC algorithms appeared in the AAP: doi.org/10.1214/25-A....
The results accommodate the 'biased progressive sampling' path selection used in @mc-stan.org.
I think this didn't get nearly enough traction. Sam did some fantastic work here leveraging the library we've been developing to make predictions for football. This was ported to a UI by Ryan Chan (Warwick MSc student) who's doing his thesis with me (on the methods behind the prediction).
The World Cup is about to start, I wrote a model using cuthbert to predict the games, check out cuthberto-carlos πβ½ ryantjx.github.io/cuthberto-ca...
I think for specialists it's also a very good chance to compare the state-space model approach with the modelling of bsky.app/profile/pymc...
I also encourage people to read the paper that makes the inference possible on our side:
arxiv.org/abs/2308.02414
New PyMC model forecasts the entire 2026 World Cup group stage: scorelines and advancement odds for all 48 teams.
Opening day it nailed Mexico 2-0 and Korea 2-1. England, Spain, and Brazil lead; Group D is chaos.
Read the full blog here: dub.sh/hBW61BZ#PyMC#WorldCup2026
Under these assumptions, we get a very simple proof of convergence, with a nice clean rate, and with lots of flexibility to account for e.g. local convergence, non-smoothness, and so on.
A British friend texted me that PinkPantheressβ dad is a statistician. Stephen G. Walker is a Bayesian. This is our chance to make Bayesian nonparametrics mainstream. Looking at you @isba-bayesian.bsky.social.
π Folks! If you are curious about the Generative Modeling via Drifting paper, but you find it difficult to understand β I wrote a different interpretation of it.
It's called: "An Expectation-Maximization interpretation of Generative Modeling via Drifting"
davidpicard.github.io/pdf/An_Expec...
The casting search for the next actor to play James Bond is officially underway, with Variety reporting that Nina Gold has been hired as the casting director for James Bond 26, which is said to be looking for a "fresh face" to play 007. https://bit.ly/4dcbcWd
Elsevier has joined a class-action lawsuit against Meta, marking the first time a major scientific publisher has sued over AI training data. The filing alleges Meta used unauthorized copies of paywalled papers and abstracts (from Common Crawl and Sci-Hub) to develop its Llama models.
#AcademicSky
Given popular demands, we have resumed the registration for a short period of time until *30 Apr*! Those already on the waiting list are guaranteed a slot so long as you register by 30 Apr. Other additional slots are available on a first-come-first basis :)
My finalist medal from the Ignyte Awards arrived today for my scifi novella "Fractal Karma" which was a finalist in 2025
Made me tear up, it's beautiful
If you want to read my story, it's available here. 2050's Boston and a hivemind based on Brunnian links: clarkesworldmagazine.com/ratnakar_10_...
Clearly a must read for anyone even remotely interested in numerical integration (be it stochastic and deterministic).
Toni has been (hyper)active in studying these methods both theoretically and practically.
arxiv.org/abs/2602.16218
Another exciting workshop to be held at Warwick Statistics this coming June: The ProbAI Theory of Scaling Laws Workshop from 22-24 June!
Website of the workshop: warwick.ac.uk/fac/sc...
Registration open until 31 March on a first-come-first-serve basis: warwick.ac.uk/fac/sc....
ELLIS Institute Finland @ellisinstitute.fi has open call for postdocs (DL Feb 9) www.ellisinstitute.fi/postdoc-recr...
There are 45 PIs to choose from, and you can apply to work also with me on computational Bayesian modeling and Bayesian workflow!
Shreya Sinha Roy's first paper (joint with me, Christian Robert and Rito Dutta) is on "Generalized Bayesian deep reinforcement learning". We use a neural network as a model in Bayesian reinforcement learning, trained using a generalized prequential scoring rule with SMC arxiv.org/abs/2412.1...
π€ Thinking about doing a PhD in statistics, probability or mathematical finance?
π Want to join a world-class doctoral programme?
Here at the Warwick Centre for Doctoral Training (CDT) in Statistics, we offer 10+ fully funded PhD studentships to talented applicants from around the globe.
Random thought: imagine there's a parallel universe exactly identical to ours. You are a genius scientist and invent a machine that lets you cross. As you press the button, your doppelganger does too, and so, for all intents and purposes, nothing changes and the machine simply doesn't work.
We @uniofjyvaskyla.bsky.social are looking for an Assistant/Associate Professor (tenure track) in Mathematics (Probability/Mathematical Foundations of Data Science): www.ellisinstitute.fi/pi-positions....
Application instructions & form: www.ellisinstitute.fi/PI-recruit-2..., DL Jan 12!
"The Principles of Diffusion Models" by Chieh-Hsin Lai, Yang Song, Dongjun Kim, Yuki Mitsufuji, Stefano Ermon. arxiv.org/abs/2510.21890
It might not be the easiest intro to diffusion models, but this monograph is an amazing deep dive into the math behind them and all the nuances