Videos

Quantum Chemistry Energy Regression with Deep Scattering Networks

Presenter
February 25, 2015
Abstract
Stéphane Mallat École Normale Supérieure The authors are: Matthew Hirn, Stephane Mallat, Nicolas Poilvert We present a novel approach to the regression of quantum mechanical energies based on a scattering transform of an intermediate electron density representation. A scattering transform is a deep convolution network computed with a cascade of multiscale wavelet transforms. It has appropriate invariant and stability properties for quantum energy regression. This new framework removes fundamental limitations of Coulomb matrix based energy regressions, and numerical experiments give state-of-the-art accuracy over planar molecules.
Supplementary Materials