POT Python Optimal Transport is 10 years old this week 🎂. Did not think when I pushed the first commit 10 years ago that it would still be here or have this impact (~11M dowloads on PyPI). Open Source Software is a marathon not a sprint. Thanks to all contributors and users (who cite it) 🥳.

Congratulations to @soniamazelet.bsky.social for her young talent l'Oreal women in science prize!

We are happy to announce that 28 workshops have been accepted for the Paris event, as part of the 102 accepted NeurIPS workshops: blog.neurips.cc/2026/08/10/a... They will take place on Sat Dec 12 + Sun Dec 13, 2026 (for Paris) The suggested deadline for Workshop submissions is close (Aug 29th)!

I'm happy to announce the #NeurIPS2026 workshop TS-LIMITS (Generalization for Time Series in Tight Settings: Latency, Inference, Memory, prIvacy and susTainability), which will be hosted in Paris, France 🇫🇷, Dec 12–13 2026! 🔗 Check out details and call for papers: ts-limits.github.io

Excited to announce that our workshop "Bridging Optimal Transport, Learning and Structured Data: Toward Geometric Distributional Learning" has been accepted at #NeurIPS2026 in Paris. ⏰Deadline: Aug 29, AoE 🔗Website with more informations: gddl-neurips-2026.github.io

Excellent Keynote by @akorba.bsky.social at Cap-Rfiap in Montpellier, France, on machine learning and distances between distributions.

We just released POT 0.9.7 with many new OT solvers including lazy and sparse exact solvers, HD Gaussians, sliced OT plans, Spectral-Grassmann OT, batch exact OT with Proximal point, BSP-OT, unbalanced 1D and semidiscrete. This is a big one! Thanks to all contributors! github.com/PythonOT/POT...

Slides for our ICML tutorial on Memorization and Generalization of Diffusion and Flow Matching Models are now available ! 🌀 memorization-generalization.github.io @quentinbertrand.bsky.social

Heading to #ICML2026 🇰🇷 and interested in diffusion models, flow matching, and their generalization capabilities? Don't miss the excellent tutorial by @mathurinmassias.bsky.social and @quentinbertrand.bsky.social on Monday! 📍 Hall D1 🗓️ Monday, July 6 🕘 9:00–11:30 AM Details: icml.cc/virtual/2026...

🎓 Doing a PhD in AI but unsure how to navigate your future career options? Join #ELIAS for Diverse Career Trajectories within Sustainable AI and AI for Sustainability. Speaker: Laetitia Chapel (IRISA 🇫🇷) 📍 Virtual Webinar 📅 20 May 🕒 15:00 - 16:30 CET 🔗 Register now at https://bit.ly/3P9CIuh

Anna Korba reçoit la médaille de bronze du @cnrs.fr pour ses travaux à l’interface entre mathématiques, statistiques et intelligence artificielle 🥉 Découvrez son portrait 👉 www.insmi.cnrs.fr/fr/cnrsinfo/... #TalentsCNRS

Our work "Busemann Functions in the Wasserstein Space" was accepted at #AISTATS2026 This is a joint work with Elsa Cazelles, Lucas Drumetz and @ncourty.bsky.social. I will be presenting it tomorrow at the poster 96, see you there! Link: openreview.net/forum?id=Xpt...

Thibaut Germain and Karim Lounici will present today at ICLR Poster Session 3 Pavilion 3 our paper introducing the Spectral-Grassmann OT that is a proper distance between linear operators dynamical systems (Koopman) seen as distributions. It can notably be used to compute barycenters of systems.

We are recruiting four positions connected to Machine Learning, Statistical Learning, and AI for Science in the Applied Mathematics department at École polytechnique. Join our vibrant community at IP Paris and Hi! Paris IA center. List below🧵 tinyurl.com/3jpw9t26

Open position: Monge Assistant Professor (Tenure track) on graph learning and/or LLMs, in the applied math dpt. at École polytechnique. Reduced teaching load, many funding opportunities, good students and academic freedom. Contact me if interested. Deadline March 23rd tinyurl.com/MongeAssista...

#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

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.

🎉 Happy to share that our work "Flowing Datasets with Wasserstein over Wasserstein Gradient Flows" was accepted at #ICML2025 as an oral! This is a joint work with the amazing Christophe Vauthier and @akorba.bsky.social ! Link: openreview.net/forum?id=I1O...

If you're at #AISTATS2025, check out the presentation by Jonathan Geuter, in collaboration with Clément Bonet, @akorba.bsky.social and @dmelis.bsky.social. 'DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows' openreview.net/forum?id=rFf... #AI #statistics #ML

DDEQs: Distributional Deep Equilibrium Models through Wasserstein...

Deep Equilibrium Models (DEQs) are a class of implicit neural networks that solve for a fixed point of a neural network in their forward pass. Traditionally, DEQs take sequences as inputs, but have...

openreview.net

⚔️ One for all and all for one ⚔️ Efficient computation of PArtial Wasserstein distances on the Line (PAWL) is accepted to @iclr-conf.bsky.social Joint work with Laetitia Chapel: we introduce an 𝑂(𝑛 𝑙𝑜𝑔 𝑛) solver for partial Optimal Transport (OT) in 1D openreview.net/forum?id=kzE... 🧵 1/2

Slicing Unbalanced Optimal Transport Clément Bonet, Kimia Nadjahi, Thibault Sejourne, Kilian FATRAS, Nicolas Courty Action editor: Benjamin Guedj https://openreview.net/forum?id=AjJTg5M0r8 #transport #outliers #optimal

The slides of my NeurIPS lecture "From Diffusion Models to Schrödinger Bridges - Generative Modeling meets Optimal Transport" can be found here drive.google.com/file/d/1eLa3...

Today something crazy happened. POT has reached 1000 citations (total) 🤩🚀. Very proud to be part of a scientific community that acknowledges open source research software. Please continue to use, cite and contribute to POT ! Small🧵below for those interested pythonot.github.io

Live! Keynote talk by Arnaud Doucet From Diffusion Models to Schrödinger Bridges West Exhibition Hall C, B3 https://buff.ly/4ga9GD7

Glad to announce that our work "Mirror and Preconditioned Gradient Descent in Wasserstein Space" was accepted at #NeurIPS2024 as a spotlight! This is a joint work with the amazing T. Uscidda, A. David, P.C. Aubin-Frankowski and A. Korba! Link: arxiv.org/abs/2406.08938

Mirror and Preconditioned Gradient Descent in Wasserstein Space

As the problem of minimizing functionals on the Wasserstein space encompasses many applications in machine learning, different optimization algorithms on $\mathbb{R}^d$ have received their counterpart...

arxiv.org