Andrej Risteski Releases PDEs 101 Notes for ML

Andrej Risteski, associate professor in the Machine Learning Department at CMU, announced that the first set of notes titled PDEs 101 for ML researchers is available. The notes derive model organism PDEs including the heat equation, advection, and Poisson equation. They cover strong, weak, and variational formulations plus numerical methods basics such as finite differences, finite elements, and explicit and implicit Euler. The announcement appeared in a reply linking directly to the materials on his site.