MSML21: Mathematical and Scientific Machine Learning

[dmm]

Starts in 5 minutes:

msml21.github.io/

No registration is needed - they are just handling it in a relaxed fashion

Comments

[dmm]

Computational Mathematics Workshop today: https://msml21.github.io/workshop_math/

I am attending this one.

Computational Physics Workshop tomorrow which I will skip...

[dmm]

First talk: discretize after you have an architecture for finding solutions, not before

This is a very good talk, deep material on "neural networks over functional spaces", good to know this...

[dmm]

Videos start to appear on "zoom share", and not on a good public channel like youtube. Password for them is posted to that Slack.

[dmm]

Second talk: moderate data - supervised learning

more difficult situations: PINN - physics-informed neural networks

The talk is so-so

[dmm]

Third talk looks good so far...

"The Modern Mathematics of Deep Learning": https://arxiv.org/abs/2105.04026

[dmm]

Talk 4 - very interesting

Replacing rules for coarse-grained evolution so that it is precise(that is, equal to coarse-graining of the high-res simulation)

Trained from high-res simulations of small pieces

"Put in as little machine learning as possible and see how far we can get"

He likes doing things in JAX: https://github.com/google/jax-cfd

Multi-step loss is essential

"Some of the problems mentioned at the beginning are still intractable, but every 1000x acceleration helps ;-) " - I love this way to formulate it