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We are very excited to announce that our workshop “#GRaM: Geometry-grounded Representation learning and generative Modeling” has been accepted to #ICML 2024. We invite papers on the following topics:

#GRaM template for Blogpost track is up on gram-workshop.github.io . Submit your blogpost on your favorite paper/s or your own in GRaM Workshop blogpost track. Accepted blogpost will be published on our website. Submission deadline 24th May AOE. #ICML2024

Excited to share that our paper “CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay” was accepted into ICML! Blaze(j) Manczak 🇵🇱🇱🇺🇪🇺 Auke Wiggers Corrado Rainone David Zhang Michaël Defferrard Taco Cohen 1/5

Come by our poster to learn more about simple+ efficient equivariant architectures! #ICLR2024

Are you interested in higher-order message passing on geometric graphs with steerable Clifford representations? Drop by our poster session2 at 16:30 7 May, Halle B #96! #ICLR2024

Gram Workshop Proceedings submission deadline extended to 31st May (AOE) 🥳. Now you get a couple extra days to polish your brilliant ideas and submit to #GRaM and get it published in ✨PMLR ✨

Go for Gram Workshop at #ICML2024 !!

📢 GRaM will now accept papers (both proceedings and extended abstracts) till 𝟑𝐫𝐝 𝐉𝐮𝐧𝐞 𝟖𝐩𝐦 𝐔𝐓𝐂 !

Final deadline extension!!! Go for 💪#GRaM 🤩 !

🥠 Excited to introduce our latest work on Equivariant Neural Fields (ENFs)! Grounding conditioning variables in geometry 🚀 Paper: arxiv.org/abs/2406.05753 Github: github.com/dafidofff/enf-… Project Page: dafidofff.github.io/enf-jax/ Details below 👇👇

🚀 Interested in time series generation?⏲️Excited to share my Google DeepMind Amsterdam student researcher project: Rolling Diffusion Models! arxiv.org/abs/2402.09470 (to appear at ICML 2024) Thanks for the great collaboration Emiel Hoogeboom, Jonathan Heek, Tim Salimans! 🧵1/4

🤔 Ever wondered why Relaxed Group Convolutions take the lead even in 𝐟𝐮𝐥𝐥𝐲 equivariant tasks? We dive deep into how the equivariance imposed on a network affects its training dynamics 🔎 👉 Take a look at our blog post for GRaM Workshop at ICML 2024 at tinyurl.com/458k7x4a

🔍 Searching for the Best Framework for GDL+TDL Methods? Look no further! Our latest GRaM Workshop at ICML 2024 blog post reveals how the #TopoX suite boosts modularity and optimizes time and memory usage for methods like Equivariant Simplicial Complexes 🚀 👉 Read here tinyurl.com/5bw3zs94

And we wrap GRaM Workshop at ICML 2024 with a social! Erik Bekkers Hannah Lawrence Oumar Kaba Alison Putri van der Linden Mona Schirmer Gabriele Cesa Julian Suk Guillermo Bernárdez Lev Telyatnikov and many many more!

Great opportunity to present our latest work on weight sharing via doubly stochastic matrices at GRaM Workshop at ICML 2024. Had a blast! Work done with Alejandro García Castellanos Sharvaree Vadgama ✈️ @ICML 2025 Thijs Kuipers Erik Bekkers . You can find it at openreview.net/forum?id=S8nQl…

🎉Happy to be in 🇨🇦Vancouver in the summer for ✨ICML2025! Ping me if you want to chat about Symmetries, GDL, Geometric representations + AI4Science, or want to look for the best ramen in town🍜! 🥁Excited to present a few exciting works at the main conference and workshops!

1. 🧠On the Importance of Embedding Norms in Self-Supervised Learning We show that 🔍🔍Embedding norms play a key role in self-supervised learning (SSL) by - Governing convergence rates during training. -Encoding network confidence — smaller norms correspond to more surprising or

2. 🌊Controlled Generation with Equivariant Variational Flow Matching Paper: openreview.net/forum?id=YSVSM… Thread: x.com/FEijkelboom/st…

3. 💪 Rapidash: Scalable Molecular Modeling Through Controlled Equivariance Breaking Presenting 💪🚀Rapidash🚀 architecture: a flexible architecture allowing for different symmetry-breaking, equivariance-breaking modes through a group convolutional architecture at

Also, presenting on behalf of Artem Moskalev 🕊️ work on Efficient Geometric deep learning architecture: ⏩⏩ Geometric Hyena Networks for Large-scale Equivariant Learning Paper: openreview.net/forum?id=jJRkk… Thread: x.com/artemmoskalev/…