One of those internships is on Gromov $\delta$-hyperbolicity for GNNs, and will be cosupervised together with Nicolas, myself and Laetitia Chapel. Take a look and spread the words !

Yesterday @tgnassou.bsky.social successfully defended his PhD thesis on domain adaptation of signals and in particular EEG. Huge congrats to him for all his work and his wonderful slides. It was a pleasure to be his advisor with @agramfort.bsky.social and I can't wait to see what he will do next!

I have several offers for Master internships / PhDs on graph ML funded by ERC MALAGA for 2026. Don't hesitate to contact me to apply! All infos here: nkeriven.github.io/malaga/

🌀🌀🌀New paper on the generation phases of Flow Matching arxiv.org/abs/2510.24830 Are FM & diffusion models nothing else than denoisers at every noise level? In theory yes, *if trained optimally*. But in practice, do all noise level equally matter? with @annegnx.bsky.social, S Martin & R Gribonval

Want to work on generative models and Earth Observation? 🌍 I'm looking for: 🧑‍💻 an intern on generative models for change detection 🧑‍🔬 a PhD student on neurosymbolic generative models for geospatial data Both starting beginning of 2026. Details are below, feel free to email me!

I’m recruiting a postdoctoral researcher on a fully funded 2-year contract. The topic is developing and implementing new parallel graph algorithms, with applications to data-driven transportation and logistics. Details and application procedure below ⬇️ Reach out if you have any questions!

Kickstarting our workshop on Flow matching and Diffusion with a talk by Eric Vanden Eijnden on how to optimize learning and sampling in Stochastic Interpolants! Broadcast available at gdr-iasis.cnrs.fr/reunions/mod...

Probably the best paper title of my career. To read with the Indiana jones soundtrack. And yes we solved and differentiated quite well 80 millions (small) Fused Gromov Wasserstein problems per epoch using a neural network on GPU.

blogbinaire.larecherche.fr/2025/10/10/l... Sur le blog binaire de La recherche Julie Josse : L’intelligence artificielle et la fabrique du savoir clinique Julie Josse a reçu le Prix Jeune Chercheur 2024 de l’Académie de Sciences.

Pétition "non à #ChatControl" à signer sur le site de l'assemblée nationale. petitions.assemblee-nationale.fr/initiatives/...

#Distinction 🏆| Charlotte Pelletier, lauréate d'une chaire #IUF, développe des méthodes d’intelligence artificielle appliquées aux séries temporelles d’images satellitaires. ➡️ www.ins2i.cnrs.fr/fr/cnrsinfo/... 🤝 @irisa-lab.bsky.social @cnrs-bretagneloire.bsky.social

Now accepted at #NeurIPS2025 :)

I am happy to share that our paper "Unsupervised Learning for Optimal Transport plan prediction between unbalanced graphs" was accepted at Neurips 2025 ! 🥳 Huge thanks to my co-authors @rflamary.bsky.social and Bertrand Thirion ! arxiv.org/abs/2506.12025 (1/5)

Vous pouvez soutenir ma proposition à la Cour des Comptes d'examiner les marchés publics de voyagistes, notamment dans l'ESR : participationcitoyenne.ccomptes.fr/processes/co...

I missed it last month! Very happy to present POT next week at PyData Paris.

I'm thrilled to announce that my #ERCStG project **Optinfinite : Efficient infinite-dimensional optimization over measures** has been accepted. Thank you @erc.europa.eu ! Many thanks also to @crestumr.bsky.social @ipparis.bsky.social for they support, as well as to my collaborators and friends.

Thanks @ellis.eu !

Maybe there should also be an equivalent EurIPS workshop www.eurips.cc for people who cannot or don't want to travel there?

Eloi Tanguy, Laetitia Chapel, Julie Delon: Sliced Optimal Transport Plans https://arxiv.org/abs/2508.01243 https://arxiv.org/pdf/2508.01243 https://arxiv.org/html/2508.01243

SKADA-Bench : Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities, has been published published in TMLR today 🚀. It was a huge team effort to design (and publish) an open source fully reproducible DA benchmark 🧵1/n. openreview.net/forum?id=k9F...

I love the #eurips initiative! But to live up to its potential, it should be accepted an official #neurips conference location (similar to Mexico City) and not just an addon! Then we would save C02, rather than adding to it!!! What can we do to achieve this?

This is awful! We need to treat our scientists better if we want to do good science. This means consistent funding for tenure that allows time for risky but novel discoveries and not only short-time projects and infinite post-docs. www.science.org/content/arti...

🚀 We are happy to organize the BERT²S workshop @neuripsconf.bsky.social 2025 on Recent Advances in Time Series Foundation Models. 🌐 berts-workshop.github.io 📜Submit by August 22 🎓Speakers and panelists: Chenghao Liu, Mingsheng Long, Zoe Piran, Danielle C. Maddix, Ameet Talwalkar, Qingsong Wen

Tommorrow Emile Pierret will present our paper "Diffusion models for Gaussian distributions: Exact solutions and Wasserstein errors". #ICML2025 Tue 15 Jul 11 a.m. West Exhibition Hall B2-B3 #W-1015. More details here: pierret.perso.math.cnrs.fr/publication/...

Interested in time series forecasting or data uncertainty quantification? Check out our latest paper with Adrien Cortés at @icmlconf ! Paper: arxiv.org/abs/2506.05515 Code: github.com/Victorletzel... Poster #2211 , Tue 15 Jul 11 a.m. PDT East #timeseries #quantization #uncertainty #icml2025

Emile Pierret, Bruno Galerne: Exact Evaluation of the Accuracy of Diffusion Models for Inverse Problems with Gaussian Data Distributions https://arxiv.org/abs/2507.07008 https://arxiv.org/pdf/2507.07008 https://arxiv.org/html/2507.07008

🔒 We’re hiring a postdoc at Inria SUSHI (Rennes, FR)! Work on formal verification of security across compilers, OS & hardware (e.g., RISC-V, CompCert). 📍 Rennes 🇫🇷 | 💶 ~€3K–3.2K/mo | 🛠️ Formal methods + security 📧 [email protected] team.inria.fr/sushi/files/... #Hiring #FormalMethods #RISC-V

Very honored to have given the keynote at the CAP 2025 conference in Dijon this morning. I talked about Domain adaptation, DA benchmark and applications of DA to sleep stating. Mostly work from the PhD of @tgnassou.bsky.social For those interested here are the slides remi.flamary.com/pres/OTDA_Ke...

@rflamary.bsky.social 's keynote at CAp'25 was a blast! A short summary in the linked post below...

Distributional Reduction paper with H. Van Assel, @ncourty.bsky.social, T. Vayer , C. Vincent-Cuaz, and @pfrossard.bsky.social is accepted at TMLR. We show that both dimensionality reduction and clustering can be seen as minimizing an optimal transport loss 🧵1/5. openreview.net/forum?id=cll...

Quentin Bertrand, Anne Gagneux, Mathurin Massias, R\'emi Emonet: On the Closed-Form of Flow Matching: Generalization Does Not Arise from Target Stochasticity https://arxiv.org/abs/2506.03719 https://arxiv.org/pdf/2506.03719 https://arxiv.org/html/2506.03719

Having a drink after the first day of the skada code sprint. Thanks to all the participants tons of nice things are coming. scikit-adaptation.github.io

Here is the recording with the slides for those interested! 🎤 youtu.be/UONvP1TL0-g?... 📊 drive.google.com/file/d/14ZIo... 📑 arxiv.org/pdf/2410.02724 @cohere.com @cohereforai.bsky.social

New paper on the generalization of Flow Matching www.arxiv.org/abs/2506.03719 🤯 Why does flow matching generalize? Did you know that the flow matching target you're trying to learn *can only generate training points*? w @quentinbertrand.bsky.social @annegnx.bsky.social @remiemonet.bsky.social 👇👇👇

It seems other authors* have just reached similar conclusions (large minibatches help for OT-CFM), using entropic-reg OT in place of our bilevel-sliced OT * Michal Klein, Alireza Mousavi-Hosseini, Stephen Zhang, @marcocuturi.bsky.social arxiv.org/abs/2506.05526

Today at 4pm, poster #36 #CVPR2025

📣 New preprint 📣 **Differentiable Generalized Sliced Wasserstein Plans** w/ L. Chapel @rtavenar.bsky.social We propose a Generalized Sliced Wasserstein method that provides an approximated transport plan and which admits a differentiable approximation. arxiv.org/abs/2505.22049 1/5

Skada Sprint Alert: Contribute to Domain Adaptation in Python 📖 Machine learning models often fail when the data distribution changes between training and testing. That’s where Domain Adaptation comes in — helping models stay reliable across domains.

I have cleaned a bit my lecture notes on Optimal Transport for Machine Learners arxiv.org/abs/2505.06589

Je sais pas si ça servira à quelque chose, mais je partage ici la réponse de John Tolan, l'un des pilotes du projet ERC sur le Coran européen, à propos de la polémique et des réactions sur le projet de recherche en question.

This is your periodic reminder to submit machine learning research to @tmlrorg.bsky.social. I’ve been both a reviewer and an author for the journal, and it feels good on both sides! High paper quality, and productive review discussions, why would I ever roll the conference dice again?

A thread on our new, also awesome, Siggraph paper "Linear-Time Transport with Rectified Flows", by K. Do, @dcoeurjo.bsky.social, P. Memari and me. Paper here: perso.liris.cnrs.fr/nicolas.bonn... Results in video: youtu.be/EcfKnSe6mhk

J'ai le plaisir d'annoncer la soutenance de mon habilitation à diriger des recherches de l'Université Gustave Eiffel, intitulée « Apprentissage de représentations à partir d'observations » le mardi 20 mai 2025 à 14h00. 😀 ℹ️ Informations pratiques : nicolas.audebert.at/files/HDR

It was received quite enthusiastically here so time to share it again!!! Our #ICLR2025 blog post on Flow Matching was published yesterday : iclr-blogposts.github.io/2025/blog/co... My PhD student @annegnx.bsky.social will present it tomorrow in ICLR, 👉poster session 4, 3 pm, #549 in Hall 3/2B 👈

Just now seeing that #AI4EO Symposium 2025 will be held in Rennes, Brittany, FR in September. Definitely an event you don’t want to miss if you want to stay in touch with recent research on AI for Earth observation 🌍

#ICLR2025 Marine Le Morvan presents "Imputation for prediction: beware of diminishing returns": poster Thu 24th arxiv.org/abs/2407.19804 Concludes 6 years of research on prediction with missing values: Imputation is useful but improvements are expensive, while better learners yield easier gains.

Forgot to say: #COLT2025 is in Lyon (France 🇫🇷), June 30–July 4. (I am not on the PC or a main organizer, just tutorials, workshops, and community events chair 🪑 this year) learningtheory.org/colt2025/wtc...

Stein's Lemma states that for a normally distributed variable X, the expected value E[Xg(X)] = E[g’(X)] for any g absolutely continuous (derivative a.e.) such that E[|g’(X)|] < ∞. It is a central result for characterizing (close-to) Gaussian data arxiv.org/abs/2104.08302

Wow, this tutorial is really a tour de force! The one I had written is super "dumbed down" as a basic intro for beginners, but to really learn the material on an intermediate/advanced level, you should check out this post...