Nicolas Courty
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ncourty.bsky.social
Nicolas Courty
@ncourty.bsky.social
200 followers 92 following 10 posts
Professor in Computer Science. Love and hate AI
Optimal Transport Affinicionado
Head of Obelix group

@Irisa
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ncourty.bsky.social
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 !
nicolaskeriven.bsky.social Nicolas Keriven @nicolaskeriven.bsky.social · 4d
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/
MALAGA: Reinventing the Theory of Machine Learning on Large Graphs (ERC StG)
nkeriven.github.io
November 7, 2025 at 1:45 PM
ncourty.bsky.social
so true....
eugenevinitsky.bsky.social Eugene Vinitsky 🍒 @eugenevinitsky.bsky.social · 19d
What if we did a single run and declared victory
Three panel thing. In the left panel we use error bars. In the second, we take statistical significance as the biggest number but still have error bars. In LLM science, we just have the biggest number
October 23, 2025 at 9:34 AM
Reposted by Nicolas Courty
cnrsinformatics.bsky.social
#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
October 8, 2025 at 9:30 AM
ncourty.bsky.social
Trying hard to decouple my interest for the scientific questions behind AI and this....😮‍💨
ketanjoshi.co Ketan Joshi @ketanjoshi.co · Sep 6
Incredible clip of tech CEOs fawning over Donald Trump. Someone store this clip in the underground archive vault
September 7, 2025 at 8:59 AM
Reposted by Nicolas Courty
olivia.science
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
September 6, 2025 at 8:13 AM
Reposted by Nicolas Courty
melaniemitchell.bsky.social
I always appreciate @cwarzel.bsky.social's takes on AI!

👀
cwarzel.bsky.social Charlie Warzel @cwarzel.bsky.social · Aug 18
Hello. I wrote a nice long essay about AI and this very strange moment where we're constantly told we're living in the dawn of a strange new future but the only thing that's actually clear is that everyone feels pretty unmoored and uncertain. I hope you'll read it
AI Is a Mass-Delusion Event
Three years in, one of AI’s enduring impacts is to make people feel like they’re losing it.
www.theatlantic.com
August 18, 2025 at 9:41 PM
Reposted by Nicolas Courty
rflamary.bsky.social
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...
June 27, 2025 at 7:44 AM
Reposted by Nicolas Courty
rflamary.bsky.social
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_...
March 26, 2025 at 7:39 AM
Reposted by Nicolas Courty
rtavenar.bsky.social
⚔️ 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
February 4, 2025 at 4:15 PM
Reposted by Nicolas Courty
tmlr-pub.bsky.social
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
January 19, 2025 at 5:07 AM