New year updates
Quite a busy semester, hence long time no posts. Lets start the year with a bunch of good news. July 2022 is going to be a busy month in Padova with the organization of IEEE WCCI 2022, including 1st Pervasive …
Category: deep learning
IJCNN 2021 papers
Our group had 4 papers recently accepted to the upcoming International Joint Conference on Neural Networks! Much work on deep learning for graphs, including a novel edge-based model, an efficient graph generation approach and an explanation method for the chemical …
Neurips 2020 WS papers
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..
Paper Accepted at COLING 2020
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!).
New JMLR paper
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!
Deep Learning for graph on Neural Networks
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!
COVID-19 Task Force
If you work in AI and you are willing to contribute to the worldwide fight against COVID-19 please consider joining the CLAIRE-COVID19 task force. I am coordinating the workgroup on omics, chemical and clinical data processing. You can have a …
Big @ESANN2020
Great success at ESANN this year, with 5 papers in: congrats to Daniele, Francesco, Federico and Marco!!
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.