ICLR2020 Paper
Our paper on benchmarking deep learning models for graph classification has been accepted at ICML 2020. Check it out!
Year: 2019
Neural networks on Treccani
Very proud of my little dissemination article on the Lingua Italiana magazine of Treccani. Check it out here (in Italian I am afraid)
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 …
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 …
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!
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.
Special session on tensor methods for deep learning @ESANN2020
I am co-organizing with Danilo Mandic a special session on “Tensor Decompositions in Deep Learning” at ESANN 2020. We welcome solid contributions and preliminary relevant results showing potential, limitations and challenges of new ideas related to the use of tensor …
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