71 citations · 73 across the 2 of their papers we have counts for
6 papers
Distributed Reinforcement Learning for Flexible and Efficient UAV Swarm Control
Federico Venturini, Federico Mason, Francesco Pase +4
Over the past few years, the use of swarms of Unmanned Aerial Vehicles (UAVs) in monitoring and remote area surveillance applications has become widespread thanks to the price redu…
Machine Learning-aided Design of Thinned Antenna Arrays for Optimized Network Level Performance
Mattia Lecci, Paolo Testolina, Mattia Rebato +2
With the advent of millimeter wave (mmWave) communications, the combination of a detailed 5G network simulator with an accurate antenna radiation model is required to analyze the r…
Enabling Simulation-Based Optimization Through Machine Learning: A Case Study on Antenna Design
Paolo Testolina, Mattia Lecci, Mattia Rebato +5
Complex phenomena are generally modeled with sophisticated simulators that, depending on their accuracy, can be very demanding in terms of computational resources and simulation ti…
On the difficulty of learning and predicting the long-term dynamics of bouncing objects
Alberto Cenzato, Alberto Testolin, Marco Zorzi
The ability to accurately predict the surrounding environment is a foundational principle of intelligence in biological and artificial agents. In recent years, a variety of approac…
Perception of visual numerosity in humans and machines
Alberto Testolin, Serena Dolfi, Mathijs Rochus +1
Numerosity perception is foundational to mathematical learning, but its computational bases are strongly debated. Some investigators argue that humans are endowed with a specialize…
Deep learning systems as complex networks
Alberto Testolin, Michele Piccolini, Samir Suweis
Thanks to the availability of large scale digital datasets and massive amounts of computational power, deep learning algorithms can learn representations of data by exploiting mult…