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.
Mark your calendars ! 🏔️Machine Learning Autumn School at Aussois (France). 🏔️ 16-21 nov 2025. Submission deadline to present your work via talk or poster: 28th of April. mlataussois.sciencesconf.org Great line-up of speakers ! ⬇️
Autumn School on Recent Advances in Machine Learning - Sciencesconf.org
mlataussois.sciencesconf.org
Mark your calendars ! 🏔️Machine Learning Autumn School at Aussois (France). 🏔️ 16-21 nov 2025. Submission deadline to present your work via talk or poster: 28th of April. mlataussois.sciencesconf.org Great line-up of speakers ! ⬇️
Autumn School on Recent Advances in Machine Learning - Sciencesconf.org
mlataussois.sciencesconf.org
Applications are open for the Machine Learning Crash Course (MLCC 2019) to be held in Genoa, the heart of the Italian riviera, on June 17-21, 2019. For more information, visit the course website atApply *BEFORE* April 19th. #MachineLearning lnkd.in/ecSCmih
📣 Hiring! I am looking for PhD/postdoc candidates to work on foundation models for science at @ULiege, with a special focus on weather and climate systems. 🌏 Three positions are open around deep learning, physics-informed FMs and inverse problems with FMs.
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