Neural quantum states for dynamics of correlated matter

The numerical simulation of correlated quantum matter, especially in two or three spatial dimensions, remains a significant challenge in computational physics. The non-equilibrium dynamics, as routinely realized for example in quantum simulators, is particularly demanding. I will discuss recent progress in simulating non-equilibrium dynamics using neural network representations of the wave function and applications to quantum phase transition dynamics of Rydberg atom arrays. Furthermore, I will sketch a pathway towards developing a neural quantum state solver for dynamical mean field theory (DMFT), which could for example become an enhancement for cluster DMFT.