AI4Science Talks

AL4PDE codebase is available @ github.com/dmusekamp/al4p…. Try it out!

🚨ICLR poster in 1.5 hours, presented by Daniel Musekamp: Can active learning help to generate better datasets for neural PDE solvers? We introduce a new benchmark to find out! Featuring 6 PDEs, 6 AL methods, 3 architectures and many ablations - transferability, speed, etc.!

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.

📰 blogpost: maxxxzdn.github.io/blog/cscnns.ht… 🕹️ google colab: colab.research.google.com/drive/1M196l6X… I tried to make the blog post more accessible than the paper and added a lot of supporting visualizations. Please check it out if you are curious about spacetime-equivariant CNNs 🚀

A new line of research towards developing algorithms & methods that enable neural operators to achieve generalization over desiderata such as PDE parameters, ICs, BCs, Geometries, Resolutions, etc. #NeuralOperators #ML4Science #PDEs #NumericalSolvers #ActiveLearning #AI4Science

Shows that active learning reduces the average error by up to 71% compared to random sampling & significantly reduces worst-case errors. Acquired datasets are reusable, providing benefits for surrogate models not involved in the data generation. Code and dataset available soon.

📢 Active Learning for Neural PDE Solvers (AL4PDE; arxiv.org/abs/2408.01536) While active learning is common in other domains, it has yet to be studied extensively for neural PDE solving. This work introduces AL4PDE, a modular and extensible active learning benchmark. #ML4PDE

Neural Spectral Methods (spectral-based neural operator + spectral loss training method) will be presented at Poster session 4 this Wed (May 8, 4:30 PM) at #ICLR2024! Paper: openreview.net/forum?id=2DbVe… Code: github.com/ASK-Berkeley/N…

Hybrid Models for Neural PDE Solving & SciML Simulations 🔥 by @ask1729 #ICML2024 #ML4Science #ML4PDEs

Panel discussion @AI_for_Science #ICML2024

Drug design @AI_for_Science by @maxjaderberg #ICML2024

PINNACLE @AI_for_Science #ICML2024

Large-scale discovery @AI_for_Science #ICML2024

Causal discovery @AI_for_Science #ICML2024

DiffusionPDE @AI_for_Science #ICML2024

Aurora @AI_for_Science #ICML2024

Happening now @AI_for_Science #ICML2024

#ML4Science and #ML4Simulations related workshops @ #ICML2024 today: Machine Learning for Life and Material Science: From Theory to Industry applications (ml4lms.bio)