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Pierre-Alexandre Mattei

@pamattei.bsky.social
1.3K followers 529 following 20 posts

Research scientist, Inria. Statistical machine learning.

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Reposted by Pierre-Alexandre Mattei
NeurIPS Europe @neuripseurope.bsky.social · 19/09/2025
Congratulations to everyone who got their @neuripsconf.bsky.social papers accepted 🎉🎉🎉 At #EurIPS we are looking forward to welcoming presentations of all accepted NeurIPS papers, including a new “Salon des Refusés” track for papers which were rejected due to space constraints!
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Pierre-Alexandre Mattei @pamattei.bsky.social · 15/09/2025
« Can you train a standard classifier without labels ? » was the question we tried to investigate in this survey. Very happy to see @louisohl.bsky.social ‘s final PhD projet published in ACM CSUR!
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NeurIPS Europe @neuripseurope.bsky.social · 01/09/2025
Is your company interested in reaching Europe's leading AI researchers? If so, don't worry! There are still plenty of opportunity to support #EurIPS as a sponsor. Sponsorship packages are available and can be further customized if necessary. More info at: eurips.cc/become-sponsor/
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Arno Solin @arnosolin.bsky.social · 12/08/2025
📣 Please share: We invite submissions to the 29th International Conference on Artificial Intelligence and Statistics (#AISTATS 2026) and welcome paper submissions at the intersection of AI, machine learning, statistics, and related areas. [1/3]
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Shubhendu Trivedi @shubhendu.bsky.social · 11/08/2025
Estimating a set’s size from uniform (or o/w well-defined) samples is a classical problem, with two well-studied extremes: min structure (birthday problem), max structure (German tank problem). A framework interpolating between them, amongst other things: arxiv.org/abs/2508.05901
arxiv.org
Estimating the size of a set using cascading exclusion
Let $S$ be a finite set, and $X_1,\ldots,X_n$ an i.i.d. uniform sample from $S$. To estimate the size $|S|$, without further structure, one can wait for repeats and use the birthday problem. This requ...
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Sam Power @spmontecarlo.bsky.social · 24/07/2025
I am pleased to announce that together with some friends, we are organising a workshop on Non-Reversible MCMC Sampling, taking place at Newcastle University from 8–10 September 2025. Details on the programme and registration can be found at the workshop website (sites.google.com/view/probai-...).
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NeurIPS Europe @neuripseurope.bsky.social · 16/07/2025
EurIPS is coming! 📣 Mark your calendar for Dec. 2-7, 2025 in Copenhagen 📅 EurIPS is a community-organized conference where you can present accepted NeurIPS 2025 papers, endorsed by @neuripsconf.bsky.social and @nordicair.bsky.social and is co-developed by @ellis.eu eurips.cc
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ELLIS @ellis.eu · 17/07/2025
📢 Present your NeurIPS paper in Europe! Join EurIPS 2025 + ELLIS UnConference in Copenhagen for in-person talks, posters, workshops and more. Registration opens soon; save the date: 📅 Dec 2–7, 2025 📍 Copenhagen 🇩🇰 🔗eurips.cc #EurIPS @euripsconf.bsky.social‬
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Hanna Wallach @hannawallach.bsky.social · 15/06/2025
Alright, people, let's be honest: GenAI systems are everywhere, and figuring out whether they're any good is a total mess. Should we use them? Where? How? Do they need a total overhaul? (1/6)
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Jean Pisani-Ferry @pisaniferry.bsky.social · 11/06/2025
Pour que les Français acceptent la nécessaire consolidation des finances publiques, il faut que la charge en soit équitablement répartie. Ma tribune @lemonde avec O. Blanchard et G. Zucman. www.lemonde.fr/idees/articl...
lemonde.fr
Olivier Blanchard, Jean Pisani-Ferry et Gabriel Zucman : « Nous partageons le constat qu’un impôt plancher sur les grandes fortunes est le plus efficace face à l’inégalité fiscale »
TRIBUNE. Le dispositif cible les centimillionnaires qui mettent en place des schémas d’optimisation pour échapper à l’impôt. Il ne fait que mettre en conformité nos lois fiscales avec le principe d’ég...
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Pierre-Alexandre Mattei @pamattei.bsky.social · 02/06/2025
The Journées de Statistique of the @statfr.bsky.social is one of my favorite conferences! It started with the Le Cam award being given to Judith Rousseau for her work on Bayesian asymptotics. Judith talked about semiparametric Bernstein-von Mises theorems and her new love for the Bayesian bootstrap.
Judith Rousseau The entrance of the campus
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Louis Ohl @louisohl.bsky.social · 12/05/2025
New preprint! Introducing "A tutorial on discriminative clustering and mutual information" With @pamattei.bsky.social and Frédéric Precioso. arxiv.org/abs/2505.04484 This preprint covers the history of discriminative clustering with pedagogical intents.
arxiv.org
A Tutorial on Discriminative Clustering and Mutual Information
To cluster data is to separate samples into distinctive groups that should ideally have some cohesive properties. Today, numerous clustering algorithms exist, and their differences lie essentially in ...
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Claire Vernade @claireve.bsky.social · 08/04/2025
We are organising EWRL in Tübingen in September. We are working on the program and we will soon be able to make first announcements. Stay tuned, follow @ewrl18.bsky.social
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antonio vergari ⚔️ short-circuiting @nolovedeeplearning.bsky.social · 04/04/2025
and what a great #PhD summer school! Thanks @jesfrellsen.bsky.social @pamattei.bsky.social and @jmtomczak.bsky.social for organizing it (and having me). Amazing talks, interactions, location and food 💙
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Pierre-Alexandre Mattei @pamattei.bsky.social · 03/04/2025
Today was the first day of invited talks of GeMSS/Statlearn @gemssai.bsky.social with great lectures by @glouppe.bsky.social and Yingzhen Li in the morning…
Gilles Louppe giving a talk.Yingzhen Li giving a talk.
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Gabriel Peyré @gabrielpeyre.bsky.social · 29/01/2025
This review paper by @guillaume-garrigos.com on SGD-related algorithms is a fantastic resource, offering elegant, self-contained, and concise proofs in a single, accessible reference. arxiv.org/pdf/2301.11235
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Pierre-Alexandre Mattei @pamattei.bsky.social · 27/01/2025
We’ve extended the Statlearn/GeMSS Spring school deadline till February 2! More details at gemss.ai
gemss.ai
Generative Modeling Summer School (GeMSS)
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Pierre-Alexandre Mattei @pamattei.bsky.social · 10/01/2025
We’re organizing once again the Gznerative Modeling Summer school this spring on the Côte d’Azur, merged for the occasion with SFdS’s Statlearn! Applications are open!
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Francis Bach @bachfrancis.bsky.social · 21/12/2024
A happy author discovering the first hard copies
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Federico Bergamin @federicobergamin.bsky.social · 09/12/2024
Heading to Vancouver for NeurIPS to present our paper “On Conditional Diffusion Models for PDE Simulation”. I'll be together with Sasha and Cristiana at poster 2500 during Thursday’s late afternoon session. Looking forward exciting discussions and meeting new people! 🥸🥸 neurips.cc/virtual/2024...
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Pierre Alquier @pierrealquier.bsky.social · 05/12/2024
Sad news. Jacques Roubaud, mathematician, poet, member of the OuLiPo, passed away today. en.wikipedia.org/wiki/Jacques...
en.wikipedia.org
Jacques Roubaud - Wikipedia
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Mathurin Massias @mathurinmassias.bsky.social · 27/11/2024
Anne Gagneux, Ségolène Martin, @quentinbertrand.bsky.social Remi Emonet and I wrote a tutorial blog post on flow matching: dl.heeere.com/conditional-... with lots of illustrations and intuition! We got this idea after their cool work on improving Plug and Play with FM: arxiv.org/abs/2410.02423
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Gaël Varoquaux @gaelvaroquaux.bsky.social · 27/11/2024
👩‍🎓👨‍🎓 Internship offers (1st step to PhD program) in my group: team.inria.fr/soda/job-off... Topics: ◼ Health AI & causality, accounting for censoring (for people who love health impact) ◼ Foundation models for tabular learning (for people into bigger models) Come work with us!
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Pierre-Alexandre Mattei @pamattei.bsky.social · 27/11/2024
Opening of the 2025 SohIA summit with @ldaudet.bsky.social on agents and generative models !
Laurent Daudet giving his talk
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Jon Barron @jonbarron.bsky.social · 25/11/2024
Our group at Google DeepMind is now accepting intern applications for summer 2025. Attached is the official "call for interns" email; the links and email aliases that got lost in the screenshot are below.
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David Picard @davidpicard.eurosky.social · 23/11/2024
This year, there are 16 positions at CNRS in computer science (8 in "applied" domains → ask me - 8 on "fundamental" domains → ask the other David). @mathurinmassias.bsky.social has a good list of advice mathurinm.github.io/cnrs_inria_a... Official 🔗 www.ins2i.cnrs.fr/en/cnrsinfo/... Don't wait!
mathurinm.github.io
Advice for CNRS and INRIA recruitment
INRIA and CNRS “chargé de recherche” positions offer unique conditions of freedom to do first-grade research: lifelong contract, no teaching involved. The application process is challenging, but it’s ...
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Pierre-Alexandre Mattei @pamattei.bsky.social · 22/11/2024
Cute 🕵️‍♂️ From Hansen and Marinacci’s discussion on « Apprroxilate models and robust decisions » by Watson & Holmes
An extract from a paper that reads: 

In their paper, Watson and Holmes (2016) follow the statistical decision approach pioneered by Wald
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Dan Roy @roydanroy.bsky.social · 19/11/2024
Some machine learners were once children. Here’s where you can find them: go.bsky.app/F6mM37U
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Franck Iutzeler @franck-iutzeler.bsky.social · 21/11/2024
📣Job altertS in Toulouse (Maths department) 📣 There are multiple jobs offers from Master internships to Assistant professor in the mathematics of data science, optimization, statistical fairness and robustness. I will try to regroup them in this thread 🧵
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Mathurin Massias @mathurinmassias.bsky.social · 21/11/2024
New blog post: the Hutchinson trace estimator, or how to evaluate divergence/Jacobian trace cheaply. Fundamental for Continuous Normalizing Flows mathurinm.github.io/hutchinson/
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Timothy Gowers @wtgowers.bsky.social · 19/11/2024
There have been several remarkable developments in combinatorics, my field of mathematics. A few weeks ago I gave a talk to a general mathematical audience in which I described six breakthroughs from the last five years. www.youtube.com/watch?v=726O...
youtube.com
Timothy Gowers, Some recent developments in combinatorics
YouTube video by Clay Mathematics Institute
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Dan Roy @roydanroy.bsky.social · 18/11/2024
I've created an initial Grumpy Machine Learners starter park. If you think you're grumpy and you "do machine learning", nominate yourself. If you're on the list, but don't think you are grumpy, then take a look in the mirror. go.bsky.app/6ddpivr
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Pierre-Alexandre Mattei @pamattei.bsky.social · 19/11/2024
This kind of figure is vastly superior to anything that can be made using TikZ, matplotlib, or ggplot. From this nice paper by Meehan and Zhang (2020), which blend measure theory, subjective Bayesian inference, and philosophy. www.jstor.org/stable/45386...
A childish but insightful drawing of a person on a boat on a lake.
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Shubhendu Trivedi @shubhendu.bsky.social · 19/11/2024
A new textbook on conformal prediction by Anastasios Angelopoulos, Rina Barber, and Stephen Bates. Looks very useful and much needed. arxiv.org/abs/2411.11824
arxiv.org
Theoretical Foundations of Conformal Prediction
This book is about conformal prediction and related inferential techniques that build on permutation tests and exchangeability. These techniques are useful in a diverse array of tasks, including hypot...
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Vincent Fortuin @vincefort.eurosky.social · 18/11/2024
I made a starter pack for Bayesian ML and stats (mostly to see how this starter pack business works). Let me know whom I missed! go.bsky.app/2Bqtn6T
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Jakub M. Tomczak @jmtomczak.bsky.social · 19/11/2024
I've created a startepack on Generative Modeling: go.bsky.app/Hd9ykTw
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Pierre-Alexandre Mattei @pamattei.bsky.social · 18/11/2024
At the end of their (technical!) book on Markov diffusion semigroups, Bakry, Gentil and Ledoux came up with an interesting epilogue: the recipe of chicken "à la Gaston Gérard". "After all, the content of this book is nothing but a sequence of recipes."
The cover of "Analysis and Geometry of Markov Diffusion Operators" by Barky, Gentil, Ledoux.Recipe of chicken "à la Gaston Gérard"
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Pierre-Alexandre Mattei @pamattei.bsky.social · 18/11/2024
Alright, let’s try out that 🦋 thing! I’ll try to post some little pieces about machine learning, uncertainty, and applied maths in general!
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