Best lab in the most wonderful city: the perfect opportunity! Come join us 🦾🌟

Checkout this cute blogpost on Jacobi fields! They were used to link Variational and Riemannian flow matching in Olga’s paper ☀️

🔮 Working on ML on curved manifolds? Don't miss out on Jacobi Fields! 🔮 I wrote a quick, highly visual and hopefully accessible introduction to the topic: "Jacobi Fields in Machine Learning" 🤠 Check it out here: olgatticus.github.io/blog/jacobi-...!

🚨2 PhD positions with me @amlab.bsky.social on learning causally grounded concepts 🚨 Are you interested in improving the #interpretability #robustness and #safety of AI by integrating #causal reasoning? Join us in beautiful Amsterdam 🇳🇱🌷🚲 Deadline: 20 April www.academictransfer.com/en/jobs/3593...

Interested in the analysis of GNN expressive power, limitations of the WL test or more in general in the definition of complete metrics on graphs? 👀 Check out this super cool work led by @martin.topology.rocks !🔥

Super happy to share our work was accepted as an Oral at the Delta Workshop @ ICLR 2025! 🎉 Can’t wait to talk about it in Singapore 😎 Congrats to the amazing team @eijkelboomfloor.bsky.social @alisometry.bsky.social @erikjbekkers.bsky.social 🔥

🤹 Excited to share Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems joint work with @wellingmax.bsky.social and @jwvdm.bsky.social preprint: arxiv.org/abs/2502.17019 code: github.com/maxxxzdn/erwin

Super excited about this project!! Amazing work by @olgatticus.bsky.social and others ❤️

Variational Flow Matching goes Riemannian! 🔮 In this preliminary work, we derive a variational objective for probability flows 🌀 on manifolds with closed-form geodesics, and discuss some interesting results. Dream team: Floor, Alison & Erik (their @ below) 💥 📜 arxiv.org/abs/2502.12981 🧵1/5

Welcome to our Bluesky account! 🦋 We're excited to announce ComBayNS workshop: Combining Bayesian & Neural Approaches for Structured Data 🌐 Submit your paper and join us in Rome for #IJCNN2025! 🇮🇹 📅 Papers Due: March 20th, 2025 📜 Webpage: combayns2025.github.io

🌟 Call for Papers – ComBayNS Workshop at IJCNN 2025 🌟 Workshop page: combayns2025.github.io We are thrilled to announce the #workshop “ComBayNS: Combining Bayesian and Neural approaches for Structured data” at the upcoming International Joint Conference on Neural Networks (#IJCNN). A thread 🧵

This is how it should be: one file, ctrl+c ctrl+v runnable from a notebook. I really do not want to mess with omegaconf, hydra or, the worst, a custom configuration system just to figure out how your model runs.

❤️❤️❤️

If you are attending #NeurIPS2024🇨🇦, make sure to check out AMLab's 11 accepted papers ...and to have a chat with our members there! 👩‍🔬🍻☕ Submissions include generative modelling, AI4Science, geometric deep learning, reinforcement learning and early exiting. See the thread for the full list! 🧵1 / 12

Come and check out our poster on the UniReps workshop at @neuripsconf.bsky.social ! Thanks again to the amazing Giovanni Marchetti, Martina Scolamiero, and Danica Kragic ❤️ See more at: arxiv.org/abs/2409.10967

🐑 Come and check out Variational Flow Matching for Graph Generation next week at @neuripsconf.bsky.social ! 🐑 Wed 11 Dec 11 a.m. PST — 2 p.m. PST West Ballroom A-D #7103 arxiv.org/abs/2406.04843

Go chat with ✨the Davids✨, super smart and cool guys!

Arxiv sharing reminder pdf ❌ abs ✅

Looking at ICLR submissions with the lowest score - What a work of art! 🧵

Meet our Lab's members: staff, postdocs and PhD students! :) With this starter pack you can easily connect with us and keep up to date with all the member's research and news 🦋 go.bsky.app/8EGigUy

🚨 Happening today! 🚨 ⏰ 4 PM CET / 10 AM EST 👩‍💻 Zoom link is in the link below 🏢 You can attend in person in L3.36, Science Park, University of Amsterdam Join us for this exciting talk! :)

Let us know if you would like to be added to the list. Looking forward to seeing the GDL community here 🦋 Also, follow @gram-org.bsky.social for GRaM workshop related updates.

A starter pack for researchers interested in Geometric Deep Learning - in the broadest sense possible! Let me know if you would like to be listed. :) Thanks @sharvaree.bsky.social for the idea! go.bsky.app/7h8sek

Yesterday, @erikjbekkers.bsky.social presented his vision on equivariance to IvI (at UvA), showcasing recent work on geometry-grounded representation learning - addressing fundamental limitations in geometric reasoning of current AI systems. 🤖 Exciting times ahead for geometric deep learning! 🌐 🤩