99 citations · 143 across the 17 of their papers we have counts for
12 papers · 1 filter
Backprop Diffusion is Biologically Plausible
Alessandro Betti, Marco Gori
The Backpropagation algorithm relies on the abstraction of using a neural model that gets rid of the notion of time, since the input is mapped instantaneously to the output. In thi…
Discrete and Continuous Deep Residual Learning Over Graphs
Pedro H. C. Avelar, Anderson R. Tavares, Marco Gori +1
In this paper we propose the use of continuous residual modules for graph kernels in Graph Neural Networks. We show how both discrete and continuous residual layers allow for more…
Jointly Learning to Detect Emotions and Predict Facebook Reactions
Lisa Graziani, Stefano Melacci, Marco Gori
The growing ubiquity of Social Media data offers an attractive perspective for improving the quality of machine learning-based models in several fields, ranging from Computer Visio…
Learning Visual Features Under Motion Invariance
Alessandro Betti, Marco Gori, Stefano Melacci
Humans are continuously exposed to a stream of visual data with a natural temporal structure. However, most successful computer vision algorithms work at image level, completely di…
On the relation between Loss Functions and T-Norms
Francesco Giannini, Giuseppe Marra, Michelangelo Diligenti +2
Deep learning has been shown to achieve impressive results in several domains like computer vision and natural language processing. A key element of this success has been the devel…
On the Role of Time in Learning
Alessandro Betti, Marco Gori
By and large the process of learning concepts that are embedded in time is regarded as quite a mature research topic. Hidden Markov models, recurrent neural networks are, amongst o…