🤹 New blog post!
I write about our recent work on using hierarchical trees to enable sparse attention over irregular data (point clouds, meshes) - Erwin Transformer, accepted to ICML 2025
blog: maxxxzdn.github.io/blog/erwin/
paper: arxiv.org/abs/2502.17019
Compressed version in the thread below:
Don's miss this exciting opportunity! 🔥
🚨Application deadline on the 15th of June
One more week to apply to this exciting position... and another position on #CausalRepresentationLearning and #ReinforcementLearning for learning provably correct #concepts from raw data opening up soon!
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...
🐳 Controlled Generation with Equivariant Variational Flow Matching
By @eijkelboomfloor.bsky.social , @zmheiko.bsky.social ,
@sharvaree.bsky.social , @erikjbekkers.bsky.social ,
@wellingmax.bsky.social , @canaesseth.bsky.social *, @jwvdm.bsky.social *
📜 As above - paper TBA soon 😉
🧵8 / 8
🌊 Exponential Family Variational Flow Matching for Tabular Data Generation
By Andrés Guzmán-Cordero*, @eijkelboomfloor.bsky.social *,
@jwvdm.bsky.social
📜 This paper will be shared soon - keep your eyes open! 🤩
🧵7 / 8
⚠️ The Perils of Optimizing Learned Reward Functions: Low Training Error Does Not Guarantee Low Regret
By Lukas Fluri*, @leon-lang.bsky.social *, Alessandro Abate, Patrick Forré, David Krueger, Joar Skalse
📜 arxiv.org/abs/2406.15753
🧵6 / 8
🔁 SDE Matching: Scalable and Simulation-Free Training of Latent Stochastic Differential Equations
By @gbarto.bsky.social , Dmitry Vetrov, @canaesseth.bsky.social
📜 arxiv.org/abs/2502.02472
🧵5 / 8
📐 On the Importance of Embedding Norms in Self-Supervised Learning
By Andrew Draganov, @sharvaree.bsky.social , Sebastian Damrich, Jan Niklas Böhm, Lucas Maes, Dmitry Kobak, @erikjbekkers.bsky.social
📜 arxiv.org/abs/2502.09252
🧵4 / 8
⚖️ A machine learning approach to duality in statistical physics
By Prateek Gupta, Andrea Ferrari, @nabiliqbal.bsky.social
📜 arxiv.org/abs/2411.04838
🧵3 / 8
🐸 Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems
By @maxxxzdn.bsky.social , @jwvdm.bsky.social , @wellingmax.bsky.social
📜 arxiv.org/abs/2502.17019
🧵2 / 8
Exciting news: AMLab is happy to have 7 papers accepted at #ICML2025! 🎉
See the thread below for the full list 📝 and meet us in Vancouver to discuss them further! 🇨🇦
🧵1 / 8
🥇 3 Best Paper Awards for AMLab members!
1. Towards Variational Flow Matching on General Geometries by @olgatticus.bsky.social et al.
2. Generative Uncertainty in Diffusion Models by @metodjazbec.bsky.social et al.
3. SDE Matching by @gbarto.bsky.social et al.
Congrats to everyone! 🔥
Test of Time Winner
Adam: A Method for Stochastic Optimization
Diederik P. Kingma, Jimmy Ba
Adam revolutionized neural network training, enabling significantly faster convergence and more stable training across a wide variety of architectures and tasks.
🤹 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
A few weeks ago, I presented SNAP at the wonderful #Bellairs Workshop on Causality in Barbados🐢
This Friday 🫰meets 🤌 as I will get to present SNAP again at the kick-off of the newest season of @causalclub.di.unipi.it! Check out this, and their other amazing upcoming talks at causalclub.di.unipi.it
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
Congratulations to "my" first PhD student Dr. @rmassidda.it who defended today at the University of Pisa *with honours* a thesis on "Methodological Advancements for Causal Abstraction Learning" 🎉
Riccardo is an amazing @ellis.eu PhD co-supervised w/ Davide Bacciu
@ellisamsterdam.bsky.social
💡 ➡️ 🧠 ➡️ 🚀
😍💥
Facts 💃🏻
The Christmas spirit has arrived at AMLab! 🎄✨
Yesterday we kicked off the holidays with a festive group dinner and a fun Secret Santa exchange. 🎅
Wishing everyone a restful and joyful winter break and a happy new year! ❄️💫
looks can be deceiving! ;)
Professor Imbens also had a mentoring session with our PhD students actively working on causality, discussing their ideas and the potential impact of their applications! 👨🔬👩🔬
@matyasch.bsky.social @roelhulsman.bsky.social @rmassidda.it @danruxu.bsky.social 🔥
Yesterday, we had the honor of hosting 2021 Nobel Laureate in Economics, Guido Imbens, at our Lab! 🤩
We had the chance to attend his inspiring talk on Experimental Design in Marketplaces 📈👩💻
A big thank you to @smaglia.bsky.social for making this event possible 💥
🧑🏫Neural Flow Diffusion Models at #NeurIPS2024 tomorrow! Discover how to build learnable noising processes for straight-line generative trajectories end-to-end and without simulations!🤯
📍West Ballroom A-D #6809
⏰Fri 13 Dec 4:30 pm — 7:30 pm
🔗https://neurips.cc/virtual/2024/poster/94656
Here are the dapper @metodjazbec.bsky.social and Alexander Timans, presenting their work on early-exit with risk control.
Come see @eijkelboomfloor.bsky.social and @gbarto.bsky.social present their work on variational flow matching now in West Ballroom A-D #7103!
François Cornet and @gbarto are presenting their work on Equivariant Neural Diffusion now at East Exhibition #2403!
Come talk to @zmheiko.bsky.social about his work on sample-efficient black box variational inference! (East Exhibition Hall #4105)
