Excellent result by our group in the upcoming NeurIPS 2020 workshops with four accepted papers.Congrats to Antonio Carta, Francesco Landolfi, Danilo Numeroso and Matteo Ronchetti! Preprints coming up..
Big graduation day in the ML family with 3 newly graduated students (two cum laude!) on topics ranging from neuro-probabilistic models for graphs, interpretability of graph neural networks for chemistry and cognitive architectures for creativity. Congratulations! Daniele Arioli, CognAC: a …
Congratulations to Daniele Castellana for having his paper accepted at COLING 2020. Check it out if you are interested in higher-order neural networks for parse trees using tensor decompositions (soon on the Arxiv!).
Review effort does not always come unnoticed.. Happy to be listed in the top third of the ICML reviewers.
Couldn’t think of a better venue for my 99th research paper than the Journal of Machine Learning Research. Check out our work on deep and probabilistic learning for graphs. Terrific job by Federico Errica!
Extremely honoured to have been nominated among the 2019 Outstanding Associate Editors of the IEEE Transactions on Neural Networks and Learning Systems. Glad to see that the effort dedicated to reviewing and editorial services does not always go unnoticed!
Very proud of the last effort from our group! Our tutorial paper on deep learning for graphs will be published as an invited paper on the Neural Networks journal! Check out a preliminary version on the Arxiv!
Congratulations to Alessio Gravina, for his joint Stanford-UNIPI thesis on deep learning for graphs hitting the news: https://www.unipi.it/index.php/news/item/17721-tesi-congiunta-con-stanford-per-un-giovane-laureato-in-informatica
While classes are suspended, University is still open and today we had a great (epidemiologically-correct) graduation day with 5 of my students having discussed their B.Sc. and M.Sc. theses. Great works on graph neural networks applied to biochemistry and social-network …