461 citations · 576 across the 4 of their papers we have counts for
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cs.LG2020
Graph-Based Neural Network Models with Multiple Self-Supervised Auxiliary Tasks
Franco Manessi, Alessandro Rozza
Self-supervised learning is currently gaining a lot of attention, as it allows neural networks to learn robust representations from large quantities of unlabeled data. Additionally…
cs.LG2018★ 61 cited
Learning Combinations of Activation Functions
Franco Manessi, Alessandro Rozza
In the last decade, an active area of research has been devoted to design novel activation functions that are able to help deep neural networks to converge, obtaining better perfor…
cs.LG2017★ 461 cited
Dynamic Graph Convolutional Networks
Franco Manessi, Alessandro Rozza, Mario Manzo
Many different classification tasks need to manage structured data, which are usually modeled as graphs. Moreover, these graphs can be dynamic, meaning that the vertices/edges of e…