I will be attending #NeurIPS2024! Feel free to ping me or the @polymathicai.bsky.social team if you want to chat about The Well 🥤or MPP 🚤! And since you like eye-catchy scientific gifs, here is a Rayleigh-Bénard convection one 😁
🥤: arxiv.org/abs/2412.00568
🚤: arxiv.org/abs/2310.02994

🌌 Bridging the gap between ML & numerical simulations!

With The Well, ML researchers can tackle advanced physics, and simulation experts explore efficient surrogates. Imagine predicting the explosion of supernova in seconds! 🌠
Let’s accelerate scientific discovery together!🤝

For ML researchers, The Well offers:
🧠 Unique benchmarks (spatial-temporal patterns ≠ natural videos)
📐 Many knowledge transfer tasks
⏳ Handling temporal variation
⚙️ Generalizing across physical parameters
This is an opportunity to advance scientific research with ML! 🚀

🤔 Why The Well?
Unlike natural datasets, scientific data is hard to gather & interpret. Evaluating a turbulent astrophysical process isn’t like judging a cat photo! 🐱
We standardized complex scientific datasets to let ML researchers focus on what matters: predicting physics. 📈

Generating cat videos is nice, but what if you could tackle real scientific problems with the same methods? 🧪🌌
Introducing The Well: 16 datasets (15TB) for Machine Learning, from astrophysics to fluid dynamics and biology.
🐙: github.com/PolymathicAI...
📜: openreview.net/pdf?id=00Sx5...