I created a video to help you get started using the APEBench suite (my recent #neurips paper) to benchmark autoregressive neural emulators for PDEs with a simple ConvNet emulation of 1D advection: youtu.be/q8fjQ4ZFynw

Our "Diffusion Graph Nets" paper has been accepted for Oral at #ICLR2025 🎉 DGNs are graph-based latent diffusion models that sample fully-developed fluid flows. Key strengths: ✅ Fast, accurate flow stats ✅ Works on unstructured meshes ✅ Learns from short simulations

Today, I had the chance to present my #NeurIPS paper "APEBench" Pasteur Labs & Inst. for Simulation Intelligence . You can find the recording on YouTube: youtu.be/wie-SzD6AJE

Just found a completely free Computational Fluid Dynamics Course Module by MathWorks !!! --> github.com/MathWorks-Teac… - enjoy ;-)

Travelling to Singapore next week for #ICLR2025 presenting this paper (Sat 3 pm nr. 538): arxiv.org/abs/2502.19611 DM me (Whova, Email or X) if you want to chat about (autoregressive) neural emulators/operators for PDE, autodiff, differentiable physics, numerical solvers etc. 😊

What is the role of memory for modeling time dependent PDEs? I will be at ICLR presenting our paper (Oral) where we study when it is beneficial for modeling time-dependent PDEs! 🔗openreview.net/forum?id=o9kqa… [Oral]: Thu 24 Apr 10:30 am @ Session 1E [Poster]: Thu 24 Apr 3 pm #617

If you're at #ICLR 2025 in Singapore, please check out our posters 🤗 I'm sure it's going to be a great conference! Have fun everyone...

If you are at ICLR and interested in ways to make denoising diffusion more efficient, please come to Vinh’s oral talk tomorrow at 11:30 in oral session 1C. It also involves backprop through ODE solvers and constrained learning.

Kanishk and I will be presenting PRDP on Saturday at 3pm at poster nr. 538.

At #ICLR2025 , check out our poster today on forecasting chaos with foundation models. Yuanzhao Zhang 章元肇 Poster #43. Thu 24 Apr, 3 - 5:30 pm in Hall 3 + Hall 2B

I wanted to highlight PBDL's brand-new sections on diffusion models with code and derivations! Great work by Benjamin Holzschuh, with neat Jupyter notebooks 👍 All the way from normalizing flow basics over score matching to denoising & flow matching. E.g. colab.research.google.com/github/tum-pbs…

This week I started as a Research Scientist Intern at Meta Reality Labs in wonderful Zurich, Switzerland🇨🇭. Let me know if you are around and want to chat about neural emulators, differentiable physics, numerical solvers, etc.

Amazing event for people at ICML. Sad I cannot attend.

Journal of Open Source Software just published our "Tesseract Core: Universal, autodiff-native software components for Simulation Intelligence", Dion Häfner Alexander Lavin 🎉 doi.org/10.21105/joss.…

🚨🚨🚨 Call for papers alert 🚨🚨🚨 The "Differentiable Systems and Scientific Machine Learning" workshop at the 1st EurIPS conference is now accepting submissions! Let's explore the intersection of differentiable programming and SciML together. differentiable-systems.github.io/workshop-eurip…

📢 Calling for (4-page) workshop papers on #differentiable programming and #SciML. This is a great opportunity to showcase your work or work in progress alongside keynote presentations by Petros Koumoutsakos, Patrick Kidger, Thuerey Group at TUM & Astrid Walle.