Pt 1: Physics-Informed Machine Learning

A hands-on post to open this series on Physics-Informed ML

I am going to do a series on Physics-Informed Machine Learning (PIML). This is an area that I am quite passionate about and have been working since for a little over 5 years. Yes, this includes PINNs, but many other things as well that I would really like to emphasize. There are many other ways we can encapsulate/obey the physics at hand into our ML surrogate modeling.

Part 1 here will focus on libraries allowing application developers to build/use ML surrogates based on physics.