131 citations · 193 across the 4 of their papers we have counts for
5 papers
A sub-sampling algorithm preventing outliers
L. Deldossi, E. Pesce, C. Tommasi
Nowadays, in many different fields, massive data are available and for several reasons, it might be convenient to analyze just a subset of the data. The application of the D-optima…
Learning Multi-Agent Coordination through Connectivity-driven Communication
Emanuele Pesce, Giovanni Montana
In artificial multi-agent systems, the ability to learn collaborative policies is predicated upon the agents' communication skills: they must be able to encode the information rece…
Improving Coordination in Small-Scale Multi-Agent Deep Reinforcement Learning through Memory-driven Communication
Emanuele Pesce, Giovanni Montana
Deep reinforcement learning algorithms have recently been used to train multiple interacting agents in a centralised manner whilst keeping their execution decentralised. When the a…
Learning to detect chest radiographs containing lung nodules using visual attention networks
Emanuele Pesce, Petros-Pavlos Ypsilantis, Samuel Withey +3
Machine learning approaches hold great potential for the automated detection of lung nodules in chest radiographs, but training the algorithms requires vary large amounts of manual…
Classifying HCP Task-fMRI Networks Using Heat Kernels
Ai Wern Chung, Emanuele Pesce, Ricardo Pio Monti +1
Network theory provides a principled abstraction of the human brain: reducing a complex system into a simpler representation from which to investigate brain organisation. Recent ad…