Robust deep learning from weakly dependent data.

Recent developments on deep learning established some theoretical properties of deep neural networks estimators. However, most of the existing works on this topic are restricted to bounded loss functions or (sub)-Gaussian or bounded variables. This paper considers robust deep learning from weakly dependent observations, with unbounded loss function and unbounded output.