I am not at #ICLR2024 but Mirco Mutti and Riccardo De Santi will present our work (w/ Alexander Marx | a-marx.bsky.social) tomorrow at 16:30! We show how to do posterior sampling in RL starting from a prior specified through a partial causal graph ➡️ more edges mean better statistical efficiency 🔥

Work on diffusion! 😜

OK, time for some tweets about distances between Markov chains! Actually this is about a preprint we've just posted on arxiv with Sergio Calo, Anders Jonsson, Ludovic Schwartz & Javier Segovia-Aguas. FFO optimal transport & bisimulation. Let's dig in! arxiv.org/abs/2406.04056 1/n

Thrilled to share our 8 conference paper contributions to ICML Conference 2024 next week. Congrats to our doctoral fellows, postdoctoral fellows, and staff members involved: Afra Amini, Manish Prajapat, Javier Abad Martinez, Konstantin Donhauser, Riccardo De Santi, Imanol Schlag, D. Dmitriev, E. Bamas

We just released our ETH Zürich AI in the Sciences and Engineering Master’s course on YouTube! 📚 Prof. Siddhartha Mishra and I explain PINNs, neural operators, foundation models, neural PDEs, diffusion models, symbolic regression, and more! #AI4Science youtube.com/watch?v=LkKvhv…

ARLET started now! Come to the first floor to join us #ICML2024

Periodic reminder that at my website you can find over 1000 pages of lecture notes on algorithms, data science, game theory, market and mechanism design, blockchain protocols, and more (see replies for link)

The final draft of Francis Bach's excellent new learning theory book is available: di.ens.fr/~fbach/ He doesn't cover VC dimension, but builds up from regression to general smooth losses, which is heresy of course, but actually fills a much-needed niche. Highly recommended!

I am hiring 3 postdocs at #KAUST to develop an Artificial Scientist for discovering novel chemical materials for carbon capture. Join this project with Francesco Faccio @ ICLR2025 🇸🇬 at the intersection of RL and Material Science. Learn more and apply: faccio.ai/postdoctoral-p…

📣We have a tenure-track faculty opening in Responsible AI at ETH CS Department: ethz.ch/en/the-eth-zur… ETH Zurich is a vibrant environment for AI research with the ETH AI Center etc. Please help spread the word!

Fully-funded #PhD in #ML at The University of Edinburgh (School of Informatics, The University of Edinburgh, ANC@Edinburgh), in 𝐠𝐞𝐨𝐦𝐞𝐭𝐫𝐢𝐜 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 and 𝐮𝐧𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 𝐪𝐮𝐚𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧. Application deadline: 15 Dec '24. Starting Sep '25. Details in the reply. Please RT and share with anyone interested!

Over the last years we understood how to control generative models via RL/control to maximize expected rewards under KL regularization. But for many applications, that’s not enough. Hence the question: can we control them further? Excited to present our ✨Oral✨ paper “Flow

Apply for the AITHYRA-CeMM International PhD Program! 15-20 fully funded PhD fellowships available in Vienna in AI/ML and Life Sciences Deadline for applications: 10 September 2025 apply.cemm.at

In a new paper with Sangyun Lee and Giulia Fanti, we study how to make use of negative reward signal in sparse reward tasks, including GSM8K examples giving 0 reward. The idea is to push the policy's new samples away from the observed negative samples with a Bayesian posterior

How can we perform generative (scientific) discovery beyond the data? Excited to present our paper “Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning” as ✨Spotlight✨ this Wednesday at NeurIPS 2025. We employ calculus of variations to