“The deep neural network designed by Professor Noé’s team is a new way of representing the wave functions of electrons. “Instead of the standard approach of composing the wave function from relatively simple mathematical components, we designed an artificial neural network capable of learning the complex patterns of how electrons are located around the nuclei,” Noé explains. “One peculiar feature of electronic wave functions is their antisymmetry. When two electrons are exchanged, the wave function must change its sign. We had to build this property into the neural network architecture for the approach to work,” adds Hermann. This feature, known as ‘Pauli’s exclusion principle,’ is why the authors called their method ‘PauliNet.’
https://phys.org/news/2020-12-artificial-intelligence-schrdinger-equation.html?
Deep Pauli?
DEEP SCRATCH (REMIX) 