Thanks to the invaluable work of my student Valerio De Caro, the code for the Hidden Tree Markov Network has been finally released. Check out Valerio’s github.
Category Archives: Students
Big AI graduation day
Today we graduated a batch of 7 students from the first cycle of our AI M.Sc. of Computer science! Congratulations to my students of the AI curriculum, Andrea Cossu, Michele Cafagna, Federico Rossetto, Silvia Severini, as well as to Francesco Landolfi, from our previous M.Sc. Degree.
Internship @Stanford
Good luck to Alessio Gravina who is starting an intership at Stanford University for his M.Sc. project, co-supervised by me and Corrado Priami as part of the Spark program.
New Graduates
Congratulations to Luigi di Sotto and Stefan Daniel Motoc for having completed their M.Sc. and B.Sc. in Computer Science with a final project on deep learning topics. Luigi discussed a novel pooling mechanism for graph convolutional networks. Stefan proposed a thorough analysis of the latent space of MusAE, our deep adversarial autoencoder for music generation.
First graduate of the AI Curriculum
Congratulations to my student Vlad Pandelea who is hitting the University headline news as first graduate (cum laude!) of the Artificial Intelligence curriculum here at the Computer Science Department.
New M.Sc. Graduates!
Congratulations to Diego Giorgini and to Vlad Pandelea for having succesfully defended their theses on a multiscale recurrent neural memory and on audio-augmented dialogue systems.
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).
Congratulations!!
First ISPR lecture
The first lecture of the 2019 edition of the Intelligent Systems for Pattern Recognition (ISPR) course will be on
THURSDAY 22/02/2019 h. 14-16 – ROOM C1 – POLO FIBONACCI
More information on the course website.
New IEEE TNNLS journal paper
Congratulations to my student Francesco Crecchi for his first journal paper showing how Dropout can be used to enforce robustness to missing inputs at test time in several recurrent neural networks. Check out its applications to sensor data processing.
Augmenting Recurrent Neural Networks Resilience by Dropout. In: IEEE Transactions on Neural Networs and Learning Systems, 2019.
Facebook internship
Congratulations to my Ph.D. student Federico Errica who has just been selected for a summer internship at Facebook. Have fun!