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 …
Category: deep learning
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..
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!).
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!
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!
Great success at ESANN this year, with 5 papers in: congrats to Daniele, Francesco, Federico and Marco!!
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..
Our paper on fragment-based molecule generation just got accepted at AISTATS 2020: congratulations to Marco Podda for the achievement! Soon on the Arxiv.
Our paper on benchmarking deep learning models for graph classification has been accepted at ICML 2020. Check it out!