Any recommendation on the research focusing on the application of stochastic process on deep learning?

For example, gradient decent can be random, and the selection of mini-batch, or the initialization of parameters can be random, so it’s easy to come out the idea that we could implement stochastic process into the development of algorithm of deep learning, or apply deep learning into solving random process… Any recommendation on the papers/methods/innovative ideas? Many thanks…