iiinova — where your digital self keeps evolving

Alexander Terenin @avt.im · 20/03/2026

Big career news: I'm leaving academia - and moving to the San Francisco Bay Area to explore something new. I've written a short blog post with a few reflections on the end of this chapter. If you'd like to catch up, now is the time to reach out! avt.im/blog/the-roa...

avt.im

The Road Less Traveled

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Viacheslav Borovitskiy @vabor112.bsky.social · 12/03/2026

Happy to share a major milestone: after years of development, we are officially launching Version 1.0 of the GeometricKernels library! To top it off, our accompanying paper has just been published in JMLR (MLOSS)! 🎉 github.com/geometric-ke...

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Alexander Terenin @avt.im · 02/02/2026

I wrote a long, detailed blog post on the state of AI and machine learning. The post's purpose is to sharpen my thinking and help ensure I work on the right things over the next few years. You might find parts of it interesting. Comments are welcome. avt.im/blog/where-a...

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Alexander Terenin @avt.im · 05/12/2025

After a delayed flight and missing my first poster, I have officially arrived at NeurIPS! I’ll present another poster tomorrow at CDE 606 from 11-2. I’ll post more on this soon. If you’re interested in meeting up, let’s get in touch!

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Alexander Terenin @avt.im · 26/10/2025

Today, I gave a talk at the INFORMS Job Market Showcase! If you're interested, here are the slides - link below! presentations.avt.im/2025-10-26-A...

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Viacheslav Borovitskiy @vabor112.bsky.social · 24/10/2025

I am hiring a fully-funded #PhD in #ML to work at the University of Edinburgh on 𝐠𝐞𝐨𝐦𝐞𝐭𝐫𝐢𝐜 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 and 𝐮𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 𝐪𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧. Application deadline: 31 Dec '25. Starts May/Sep '26. Details in the reply. Pls RT and share with anyone interested!

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Alexander Terenin @avt.im · 29/09/2025

Paper update: our recent work on Thompson sampling has a shiny new - and I hope much better - name! This new name does much better job of emphasizing what we actually do. Joint work with Jeff Negrea. Thread below!

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Alexander Terenin @avt.im · 17/07/2025

At ICML, we're presenting a paper on uncertainty-aware surface reconstruction! Compared to previous approaches, we are able to completely remove the need for recursive linear solves for reconstruction and interpolation, using geometric GP machinery. Check it out!

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Alexander Terenin @avt.im · 02/06/2025

This week’s virtual seminar on Bayesian Decision-making and Uncertainty is happening now! Noémie Jaquier (KTH Royal Institute of Technology) On Riemannian Latent Variable Models and Pullback Metrics Livestream link: www.youtube.com/watch?v=61Be...

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Alexander Terenin @avt.im · 30/05/2025

We've got a major update to our preprint on adversarial regret guarantees for Thompson sampling! As before, I think this is one of the most important projects I've worked on due to new algorithmic primitives that it - in principle - unlocks. Thread below on what's new!

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Alexander Terenin @avt.im · 29/05/2025

We’d like to announce next week’s virtual seminar on Bayesian Decision-making and Uncertainty! Noémie Jaquier (KTH Royal Institute of Technology) On Riemannian Latent Variable Models and Pullback Metrics Sign-up link: gp-seminar-series.github.io

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Alexander Terenin @avt.im · 26/05/2025

This week’s virtual seminar on Bayesian Decision-making and Uncertainty is happening now! Marvin Pförtner (University of Tübingen) Computation-Aware Kalman Filtering and Smoothing YouTube livestream: www.youtube.com/watch?v=0tG2...

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Alexander Terenin @avt.im · 23/05/2025

We’d like to announce next week’s virtual seminar on Bayesian Decision-making and Uncertainty! Marvin Pförtner (University of Tübingen) Computation-Aware Kalman Filtering and Smoothing Sign-up link: gp-seminar-series.github.io

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Alexander Terenin @avt.im · 19/05/2025

This week’s virtual seminar on Bayesian Decision-making and Uncertainty is happening now! Yingzhen Li (Imperial College London) On "Modernising" Sparse Gaussian Processes YouTube livestream: www.youtube.com/watch?v=VbGW...

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Alexander Terenin @avt.im · 14/05/2025

We’d like to announce next week’s virtual seminar on Bayesian Decision-making and Uncertainty! Yingzhen Li (Imperial College London) On Modernising Sparse Gaussian Processes Sign-up link below!

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Alexander Terenin @avt.im · 12/05/2025

This week’s virtual seminar on Bayesian Decision-making and Uncertainty is happening now! Sebastian Ament (Meta) Unexpected Improvements to Expected Improvement for Bayesian Optimization YouTube livestream: www.youtube.com/watch?v=B71O...

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Alexander Terenin @avt.im · 07/05/2025

We’d like to announce next week’s virtual seminar on Bayesian Decision-making and Uncertainty! Sebastian Ament (Meta) Unexpected Improvements to Expected Improvement for Bayesian Optimization Sign-up link: gp-seminar-series.github.io

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Alexander Terenin @avt.im · 05/05/2025

This week’s virtual seminar on Bayesian Decision-making and Uncertainty is happening now! Paul Jensen (University of Michigan) Exploring phenotypes and genotypes with a robot scientist YouTube livestream: www.youtube.com/watch?v=UJQ2...

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Alexander Terenin @avt.im · 01/05/2025

We’d like to announce next week’s virtual seminar on Bayesian Decision-making and Uncertainty! Paul Jensen (University of Michigan) Exploring phenotypes and genotypes with a robot scientist Sign-up link below! gp-seminar-series.github.io

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Alexander Terenin @avt.im · 30/04/2025

PSA: If your GitHub Pro account expires - for instance due to a slow edu discount renewal - your GitHub Pages will go offline ***and might redirect to a SPAM website***! I have no idea technically how. If you land in this situation, move your DNS off GH pages immediately!

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Alexander Terenin @avt.im · 24/04/2025

Online learning is like magic

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Alexander Terenin @avt.im · 14/04/2025

This week’s virtual seminar on Bayesian Decision-making and Uncertainty is happening now! Qian Xie (Cornell University) Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index www.youtube.com/watch?v=T2IT... gp-seminar-series.github.io

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Alexander Terenin @avt.im · 09/04/2025

We’d like to announce next week’s virtual seminar on Bayesian Decision-making and Uncertainty! Qian Xie (Cornell) Cost-aware Bayesian Optimization via the Pandora's Box Gittins Index Sign-up link here: gp-seminar-series.github.io

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Alexander Terenin @avt.im · 07/04/2025

This week’s virtual seminar on Bayesian Decision-making and Uncertainty is happening now! Frank Hutter (University of Freiburg) Accurate predictions on small data (and time series) with the tabular foundation model TabPFN YouTube: www.youtube.com/watch?v=SOXK... gp-seminar-series.github.io

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Alexander Terenin @avt.im · 02/04/2025

We’d like to announce next week’s virtual seminar on Bayesian Decision-making and Uncertainty! Frank Hutter · University of Freiburg Accurate predictions on small data (and time series) with the tabular foundation model TabPFN Sign-up link below! gp-seminar-series.github.io

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Kamilė Stankevičiūtė @kamile.st · 06/03/2025

Excited to announce our new work on reasoning and retrieval evaluation in LLMs! 😊 Check it out!

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Alexander Terenin @avt.im · 21/02/2025

New preprint! This is a hardcore technical paper on Thompson sampling - as a strategy for the so-called online learning game. I think it's one of the most long-term important things I have ever worked on due to what it makes possible. That needs explaining: thread below! arxiv.org/abs/2502.14790

arxiv.org

An Adversarial Analysis of Thompson Sampling for Full-information Online Learning: from Finite to Infinite Action Spaces

We develop an analysis of Thompson sampling for online learning under full feedback - also known as prediction with expert advice - where the learner's prior is defined over the space of an adversary'...

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Marcin Wichary @aresluna.org · 14/02/2025

I think every designer should write a love letter to a font at least once in their lifetime. This is mine: A 150-year-old font you have likely never heard of, and one you probably saw earlier today. aresluna.org/the-hardest-...

aresluna.org

The hardest working font in Manhattan

A story of a 150-year-old font you have never heard of – and one you probably saw earlier today.

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Kacper Wyrwal @wyrwalkacper.bsky.social · 13/02/2025

Excited to share our ICLR 2025 oral "Residual Deep Gaussian Processes on Manifolds"! With @vabor112.bsky.social & @arkrause.bsky.social, we introduce manifold-to-manifold GPs that can be composed together, generalising deep GPs to manifolds. Applications include wind prediction & Bayes opt! 1/n

Schematic illustration of a scalar-valued residual deep GP with L hidden layers. The last layer is a scalar-valued GP on the manifold. If it is not present, the model is manifold-valued. If it is replaced with a Gaussian vector field (GVF), the model is a vector field on the manifold.

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Viacheslav Borovitskiy @vabor112.bsky.social · 29/01/2025

Good news! GeometricKernels now supports the new 𝑯𝒐𝒅𝒈𝒆-𝒄𝒐𝒎𝒑𝒐𝒔𝒊𝒕𝒊𝒐𝒏𝒂𝒍 𝒌𝒆𝒓𝒏𝒆𝒍𝒔 for flow-type data on graphs (thnx Maosheng Yang). Example notebook: geometric-kernels.github.io/GeometricKer.... For the theory behind, see arxiv.org/abs/2310.19450. Some details below.

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Thomas Dickerson @elfprince13.mumak.app · 16/01/2025

I will not be taking any questions at this time

D&D alignment chart
Lawful good: Rust | Neutral Good: Racket | Chaotic Good: Haskell.
Lawful Neutral: Scala | True Neutral: Java | Chaotic Neutral: Typescript.
Lawful Evil: C++ | Neutral Evil: Python | Chaotic Evil: PHP.

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samuel mehr @mehr.nz · 04/01/2025

not really related I know but just had a look at the article metrics and here's some decent evidence science twitter has moved fully to bsky

altmetric for this article, with only 64 tweets and 426 skeets

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Alexander Terenin @avt.im · 22/12/2024

I have been saying for years: getting into deep learning to chase high-salary AI jobs where you can do what you want is a fool’s errand. There’s a lot of competition, differentiating yourself except by luck or connections is hard, and most companies want direct benefit from the salaries they pay.

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Alexander Terenin @avt.im · 21/12/2024

I'm looking for an emergency reviewer or two for an AISTATS submission in the area of Bayesian ML theory, which at present has the misfortune of three low-quality reviews. If you're able to help, please DM and let me know! Please link your Google Scholar if I don't already know you personally.

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Alexander Terenin @avt.im · 19/12/2024

Given the hype, I'd like to see Google's genAI search results become a lot better. I recently rented a car, and searched whether it has wireless CarPlay. Google's genAI results say "yes it does" while manufacturer's website says no. LLMs getting facts right is still a problem.

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Viacheslav Borovitskiy @vabor112.bsky.social · 19/12/2024

Check out the workshop "Uncertainty in multivariate, non-Euclidean, and functional spaces: theory and practice" Where: Isaac Newton Institute, Cambridge When: 6-9 May 2025 Application deadline: 12 Jan 2025. Link in reply (contributed talks/posters are welcome) I will be there!

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Gergely Neu @neu-rips.bsky.social · 17/12/2024

i recently gave a talk about questions like this at a workshop organized by the amazing "learning theory alliance" (let-all.com), and several students reached out to tell me how much my talk resonated with them. link to the slides here: docs.google.com/presentation...

docs.google.com

let-all-gergo

Research styles: “fast” or “slow”? Some thoughts by Gergely Neu

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Naomi Saphra @nsaphra.bsky.social · 17/12/2024

my most controversial take is that the whitespace margin provided by your LaTeX template is often totally reasonable and you don't need to add negative \vspace everywhere by default out of habit

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Alexander Terenin @avt.im · 15/12/2024

At the NeurIPS optimization workshop. In my opinion, the “most creative poster design” award should go to these folks:

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Renato Berlinghieri @renberlinghieri.bsky.social · 15/12/2024

Virginia Aglietti is the last invited speaker at our workshop in Bayesian decision making and uncertainty #NeurIPS2024 join us in East room 8 to hear her talk on FunBO, a new way to discover acquisition functions for Bayesian optimization!

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

Our next invited speaker is Jacob Gardner talking about how Bayesian optimization needs better deep learning! #NeurIPS2024

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

We are super excited to have Roman Garnett telling us what he learned while writing his Bayesian optimisation book at our workshop in Bayesian decision making and uncertainty! Come join us in East room 8 or online #NeurIPS2024

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

Our last contributed talk is "Variational Search Distributions" by Rafael Oliveira! #NeurIPS2024

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

Joachim Schaeffer is the next contributed speaker at our Bayesian decision making and uncertainty workshop #NeurIPS2024, talking about how to use spatiotemporal Gaussian processes for Lithium-Ion battery system health monitoring!

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

Patrick O’Hara is now talking about "Distributionally Robust Optimisation with Bayesian Ambiguity Sets" at the Bayesian decision making and uncertainty workshop #NeurIPS2024

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

Freddie Bickford Smith is now talking about "Rethinking Aleatoric and Epistemic Uncertainty" at our workshop in Bayesian decision making at uncertainty!

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

Ruda Zhang is the next contributed speaker at our Bayesian decision making at uncertainty workshop! He is presenting work joint with his PhD student Taiwo Adebiyi on Gaussian process Thompson sampling via rootfinding.

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

@miniapeur.bsky.social is now giving the first contributed talk for our Bayesian decision making and uncertainty workshop #NeurIPS2024! Join us to hear about how to convert graphs into Hodgelet spectral features and do classification using Gaussian processes!

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Renato Berlinghieri @renberlinghieri.bsky.social · 14/12/2024

@estherrolf.bsky.social is the next speaker at the #NeurIPS2024 workshop in Bayesian decision making at uncertainty -- come to East Room 8 now or online to hear why we need more uncertainty based modeling in geospatial machine learning!

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