*Alice's book got a (minor) upgrade!* Thanks to the dozens of people who gave feedback, now with 1000% less typos and errors, a novel set of Colab lab sessions, and a brand-new CC-BY-SA license. 🙃 sscardapane.it/alice-book/

The chapter on automatic differentiation is my favorite!

📢We are very excited to announce a ✨two-day TAG event ✨(alongside NeurIPS) in San Diego! Join us for an exciting two days filled with incredible speakers, panelists, and multiple poster sessions. 🌟Submission deadline is 1st October AOE. Call for papers is here!

Due to a record # of submissions for our NeurIPS workshop on Symmetry & Geometry in Neural Representations (neurreps.org), we're looking for volunteers to serve as Reviewers. So many phenomenal submissions. Send me your OpenReview email if you'd like to contribute!

The Topological Deep Learning Challenge is BACK! And this time, we're talking new data: new domains, new tasks, and much more! Not only is this the most ambitious, interdisciplinary edition yet... but there's 💰 prizes and internship opportunities on the line. See you there!

The Topological Deep Learning Challenge is back!🍩🤖 Bigger, bolder, and ready to expand the impact of TDL for science & engineering. By Guillermo Bernárdez Lev Telyatnikov Mathilde Papillon🦋 mathildepapillon .bsky .social Miquel Ferriol Marco Montagna Raffael Theiler Olga Fink TAGinDS Geometric Intelligence Lab & Arlequin AI!

Prizes, research gigs, and a chance to twist data into new shapes with topology + ML? 👾 Count me in for the Topological Deep Learning Challenge 2025! 🌀 Who else is ready to expand the data universe?

We are ✨42✨ days away from the Topological Deep Learning Challenge deadline! Not sure where to start? Participating is as simple as implementing an existing graph dataset :) Win cash prizes up to 800$ USD graciously offered by #ArlequinAI or internships at UCSB and EPFL

Thrilled to see these two papers by Simon Mataigne co-authored with P.-A. Absil published this month 🤩 They connect deep mathematical theory to practical algorithms on the Stiefel manifold and the approximation of the Riemannian barycenter 🌐 Details & papers👇Geometric Intelligence Lab

Cool news: our extended Riemannian Gaussian VFM paper is out! 🔮 We define and study a variational objective for probability flows 🌀 on manifolds with closed-form geodesics. Floor Eijkelboom Alison Cong Liu Max Welling Jan-Willem van de Meent Erik Bekkers 🔥 📜 arxiv.org/abs/2502.12981

🚨 20 DAYS LEFT to submit to the Topological Deep Learning Challenge! TopoBench just hit 200 stars 🌟, and we're looking forward to seeing your submissions before the deadline. This year's challenge has multiple ways to contribute and prizes. All details: geometric-intelligence.github.io/topobench/tdl-…

Interested in Topological Deep Learning?🍩 20 days is more than enough to participate in the Topological Deep Learning challenge 2025! Details (including prizes) below 🌟 Geometric Intelligence Lab The Robert Mehrabian College of Engineering UC Santa Barbara EPFL Mathilde Papillon🦋 mathildepapillon .bsky .social Guillermo Bernárdez Lev Telyatnikov

🚀Don’t miss out on the Topological Deep Learning Challenge 2025! 20 days left to submit – more than enough time to make your mark🍩 👇See details and prize info below🌟 Geometric Intelligence Lab The Robert Mehrabian College of Engineering UC Santa Barbara EPFL Mathilde Papillon🦋 mathildepapillon .bsky .social Guillermo Bernárdez Lev Telyatnikov