Nov 27, 2016

I am working on a project (using Julia) to "learn" an efficient representation of scale invariant many-body quantum states from a microscopic Hamiltonian. The particular structure being learned is supposed to be highly efficient both in representational complexity and computational complexity for predicting physical observables. (Work in progress at )

Also reading/thinking about ideas at the heart of theoretical physics and machine learning. In particular, I've spent the last several months in trying to understand the following two papers in increasing levels of depth