From Boltzmann machines to Born machines*

Statistical physics has made profound impacts on machine learning, e.g., energy-based models for generative modeling and mean-field approaches for variational inference. We argue that quantum physics can be equally inspirational by exploiting mind-provoking analogies between the "image space" and the Hilbert space. Exchanging of ideas, insights, techniques, and even intuitions developed for machine learning and quantum physics will cross-fertilize both research fields. In particular, I shall talk about quantum inspired generative models with explicit and implicit probability densities.