Great success at ESANN this year, with 5 papers in: congrats to Daniele, Francesco, Federico and Marco!!

# Category Archives: deep learning

# Amused by MusAE

Our work on MusAE, an adversarial autoencoder for music generation, has just been accepted at ECAI2020. Congratulations to Andrea for his first paper! Soon on the Arxiv..

# AISTATS2020 Paper

Our paper on fragment-based molecule generation just got accepted at AISTATS 2020: congratulations to Marco Podda for the achievement! Soon on the Arxiv.

# ICLR2020 Paper

Our paper on benchmarking deep learning models for graph classification has been accepted at ICML 2020. Check it out!

# Learning for graphs session @WCCI2020

I am happy to announce that I will be co-organizing a WCCI-2020 special session on Learning Representations for Structured Data together with Filippo Maria Bianchi (UIT), Thomas Gärtner (University of Nottingham), Nicolò Navarin (University of Padova) and Alessandro Sperduti (University of Padova)

Paper submission deadline is 15 January 2020 (extension pending).

Send you work through the conference submission site!

# HTN code

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.

# 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.

# New H2020 Project

Now it looks official enough that I am going to coordinate the H2020 project TEACHING “A computing toolkit for building efficient autonomous applications leveraging humanistic intelligence”. Project will start on January 2020. Stay tuned!

# Researcher of the month

I am honoured that Università di Pisa has chosen me for the highlights of the Researcher of the Month for September 2019.

# New accepted papers

A bunch of new papers on deep learning for graphs and neural language processing has just been accepted for publication. Check them out!