Event Details

There is information to be gained by studying how well a neural network is able to learn physics data. I will discuss the 'learning by confusion' method and its extension to 'discriminative cooperative networks'. Both of these methods rely on the ability to order physics data along one or multiple tuning parameters, which is a feat that is often impossible in non-physics data-sets. In the second part, I will describe how reinforcement learning methods may help in quantum error decoding/correction.