Earlier quoted context omitted.
What library are you using for automatic differentiation. I am working on building code to optimize (and later build) high quality finite element meshes for structural analysis. For the initial proof of concept, I am simply doing finite differences, but would prefer to eventually add AD. I am unsure which packages are suitable (currently all numpy and scipy).
Both in the python version and so far in c++, I am using my own forward mode implementation in Numpy and Eigen, respectively. (Why? Well, it was easy, I wanted to learn, it’s been fast enough, and most critically, allowed me to extend it by using interval valued numbers underneath the AD variables) Here’s where I do something kind of funny In the AD implementation: Basically just write a class that overloads all the…
I use FEMAP at my day job have found Laplacian smoothing and FEMAPs other built in tools have been wanting.
I am currently thinking that my goal is to try and use reinforcement learning to build high quality meshes. In order to do that you need a loss function and if you are building a loss function you might as well wrap an optimizer around it.