iiinova — where your digital self keeps evolving

Reposted by Nicolas Courty

Clément Bonet @clement-bonet.bsky.social · 21/07/2026

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

0116

Reposted by Nicolas Courty

lebellig @lebellig.bsky.social · 21/07/2026

The last project of my PhD is finally out! 🪴 It was a pleasure collaborating with Aimi on this work! We introduce A²BM: Alignment-Aware Bridge Matching, a new framework for image-to-image translation with weakly aligned image pairs. Paper 📄: arxiv.org/pdf/2607.16294

1144

Reposted by Nicolas Courty

Gabriel Peyré @gabrielpeyre.bsky.social · 16/06/2026

The alpha version of my new book "Optimal Transport for Machine Learners" is out, with in particular an online version with interactive figures www.gpeyre.com/ot4ml/

09843

Reposted by Nicolas Courty

Clément Bonet @clement-bonet.bsky.social · 02/05/2026

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...

053

Reposted by Nicolas Courty

NeurIPS Conference @neuripsconf.bsky.social · 23/03/2026

Following the success of the EurIPS and NeurIPS-Mexico City pilots in 2025, we are thrilled to announce two official NeurIPS 2026 satellite events for this year! These will be held in Paris, France and Atlanta, USA, respectively, running alongside the main venue in Sydney, Australia.

neurips.cc

2025 Conference

The Thirty-Ninth Annual Conference on Neural Information Processing Systems

27017

Reposted by Nicolas Courty

Rémi Flamary @rflamary.bsky.social · 06/02/2026

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

tinyurl.com

Calliopé

11218

Reposted by Nicolas Courty

Marianne Blanchard @mblanchard.bsky.social · 27/01/2026

"On meurt dans mon Université", par la présidente de l'Université Paul Valéry à Montpellier. Parce que les baisses de financement des universités ce sont aussi des conditions de travail si dégradées qu'elles en deviennent intenables

04641

Reposted by Nicolas Courty

ELLIS @ellis.eu · 19/12/2025

🏹 Job alert: 3 PhD positions in AI, Earth Observation, and Science-Policy interface 📍 Vannes 🇫🇷 & Ispra 🇮🇹 📅 Apply by Jan 15th 🔗 www-obelix.irisa.fr/job-offers

www-obelix.irisa.fr

Job offers – OBELIX

087

Nicolas Courty @ncourty.bsky.social · 07/11/2025

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 !

1103

Reposted by Nicolas Courty

CNRS Sciences informatiques @cnrsinformatics.bsky.social · 08/10/2025

#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

0115

Nicolas Courty @ncourty.bsky.social · 07/09/2025

Trying hard to decouple my interest for the scientific questions behind AI and this....😮‍💨

1100

Reposted by Nicolas Courty

Olivia Guest · Ολίβια Γκεστ @olivia.science · 06/09/2025

Finally! 🤩 Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia: doi.org/10.5281/zeno... We unpick the tech industry’s marketing, hype, & harm; and we argue for safeguarding higher education, critical thinking, expertise, academic freedom, & scientific integrity. 1/n

Abstract: Under the banner of progress, products have been uncritically adopted or
even imposed on users — in past centuries with tobacco and combustion engines, and in
the 21st with social media. For these collective blunders, we now regret our involvement or
apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we
are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not
considered a valid position to reject AI technologies in our teaching and research. This
is why in June 2025, we co-authored an Open Letter calling on our employers to reverse
and rethink their stance on uncritically adopting AI technologies. In this position piece,
we expound on why universities must take their role seriously toa) counter the technology
industry’s marketing, hype, and harm; and to b) safeguard higher education, critical
thinking, expertise, academic freedom, and scientific integrity. We include pointers to
relevant work to further inform our colleagues.

Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI
(black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are
in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are
both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and
Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf.
Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al.
2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA).

Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms
are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe.

Protecting the Ecosystem of Human Knowledge: Five Principles

11341482054

Reposted by Nicolas Courty

Melanie Mitchell @melaniemitchell.bsky.social · 18/08/2025

I always appreciate @cwarzel.bsky.social's takes on AI! 👀

0428

Reposted by Nicolas Courty

Rémi Flamary @rflamary.bsky.social · 27/06/2025

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...

1329

Reposted by Nicolas Courty

Rémi Flamary @rflamary.bsky.social · 26/03/2025

We have been reworking the Quickstart guide of POT to show multiple examples of OT with the unified API that facilitates access to OT value/plan/potentials. It allows to select regularization/unbalancedness/lowrank/Gaussian OT with just a few parameters. pythonot.github.io/master/auto_...

03211

Reposted by Nicolas Courty

Romain Tavenard @rtavenar.bsky.social · 04/02/2025

⚔️ 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

Solutions to the PAWL problem in 1D for different amounts of mass to be transported

1138

Reposted by Nicolas Courty

TMLR Published Papers @tmlr-pub.bsky.social · 19/01/2025

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

0106