A fantastic opportunity to join us in #Amsterdam for some hardcore #uncertainty in #AI 🦾🚲🌷✖️✖️✖️ #causality #tractable #probabilistic #models #neurosymbolic #imprecise #probabilities #statistical #methods and more

Two month flew by since the start of the PhD journey with @pseudomanifold.topology.rocks and now the time is right to share how our collaborations officially started, with a question: How can we measure difference in (attributed) graphs beyond binary isomorphism testing ? 🌀

There's an increasingly popular argument saying that for 3D point clouds with rotational ambiguity (e.g. molecular data) standard transformers are preferable over equivariant models for compute reasons. With “Platonic Transformers” we show why this doesn't have to be true. arxiv.org/abs/2510.03511

Enschede crowd you don't want to miss this! Join us for two exciting talks by Jolanda Wentzel and @erikjbekkers.bsky.social. As a bonus, you get to see me in "appropriate traditional dress from [my] country of origin". 📅 28 May 📍 UTwente campus

New PhD position at the University of Amsterdam in @amlab.bsky.social on learning concepts with theoretical guarantees using #causality and #RL with me, Frans Oliehoek (TU Delft) and Herke van Hoof 💥 Deadline: 15 June werkenbij.uva.nl/en/vacancies...

💬 Join TODAY’s webinar: “Symmetry, scale, and science: A geometric path to better AI" by @erikjbekkers.bsky.social & @jobrandstetter.bsky.social (ELLIS Program “Geometric Deep Learning”) 🗓️ Mon, March 10, 2025 🕓 16:00-17:00 CET 🔗 Register here: aiforgood.itu.int/event/symmet...

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 be part of this project led by Praneeta Konduri! We’re using state-of-the-art generative models to create synthetic vasculature geometries—pushing stroke treatment development forward while cutting down on patient data reliance. Exciting stuff! 😃 rdt.uva.nl/research/res...

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

Common beliefs about equivariant networks for image input include 1) They are slow. 2) They don’t scale to ImageNet. 3) They are complicated. In my opinion, these three are all false. To argue against them, we made minimal modifications to popular vision models, turning them mirror-equivariant.

Really excited about this! We note a connection between diffusion/flow models and neural/latent SDEs. We show how to use this for simulation-free learning of fully flexible SDEs. We refer to this as SDE Matching and show speed improvements of several orders of magnitude. arxiv.org/abs/2502.02472

✨ The VIS Lab at the #University of #Amsterdam is proud and excited to announce it has #TWELVE papers 🚀 accepted for the leading #AI-#makers conference on representation learning ( #ICLR2025 ) in Singapore 🇸🇬. 1/n 👇👇👇 @ellisamsterdam.bsky.social

Accepted to ICLR 🚨 Does using more geometry always help with molecule property prediction? In practice, we deal with imperfect geometries, which introduce structural noise. In our work arxiv.org/abs/2410.11933, we investigate when and how geometric information is useful (or not) for RNA molecules.

🔥 3/4 #ICLR2025 Grounding Continuous Representations in Geometry: Equivariant Neural Fields (ENF), for geometry-informed continuous signal representations openreview.net/forum?id=A4e... [email protected], @davidmknigge.bsky.social @erikjbekkers.bsky.social S. Papa, R. Valperga, S. Vadgama

🚀 AI for Good Webinar Launch: From Molecules to Models Next week, ELLIS kicks off a new webinar series on AI in life sciences, showcasing key research from ELLIS Programs. 🗓️ Date: Feb 3, 2025 🕓 Time: 16:00-17:30 CET Register: aiforgood.itu.int/event/unlear...

♻️Learning Symmetries via Weight-sharing with Doubly Stochastic Tensors by Putri van der Linden, @algarciacast.bsky.social, @sharvaree.bsky.social, Thijs P. Kuipers, @erikjbekkers.bsky.social 🪪https://neurips.cc/virtual/2024/poster/96699 📜https://arxiv.org/abs/2412.04594 🧵9/ 12

🐑 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

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

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

Soon, @erikjbekkers.bsky.social and @davidmknigge.bsky.social will give a talk elaborating even further on geometry-grounded representation learning in a NeurReps seminar. Make sure to mark the date! :) ⏰ November 21st, 4 PM CET 🔗 www.neurreps.org/speaker-seri...