I recently presented the following poster at conference in Leipzig about the potential for using representational learning for studying biological neural information processing. The main idea is to use state of the art machine learning methods to generate hypotheses about neural information processing. These hypotheses can then be tested with neuroimaging experiments.
Experiments in deep learning for speech synthesis
Jessica Thompson's journal for IFT6266 – Representation Learning at Université de Montréal
Experiments in deep learning for speech synthesis 