New ML graduates

Congratulations to two of my students who succesfully defended their B.Sc. and M.Sc. theses with two excellent ML projects.

Lorenzo Marsicano developed microESN, a library for the development of recurrent neural networks in embedded systems with minimal memory and computational resources.

Andrea Valenti designed a new deep learning model for MIDI music generation, beautifully named MusAE, for Music Adversarial autoEncoder (and of course to honour Greek mythology).