Rates and architectures for learning geometrically non-trivial operators

T. Mitchell Roddenberry, Leo Tzou, Ivan Dokmanić +2

Deep learning methods have proven capable of recovering operators between high-dimensional spaces, such as solution maps of PDEs and similar objects in mathematical physics, from v…