38 citations · 86 across the 8 of their papers we have counts for
8 papers
On the adaptation of recurrent neural networks for system identification
Marco Forgione, Aneri Muni, Dario Piga +1
This paper presents a transfer learning approach which enables fast and efficient adaptation of Recurrent Neural Network (RNN) models of dynamical systems. A nominal RNN model is f…
Real-time Classification from Short Event-Camera Streams using Input-filtering Neural ODEs
Giorgio Giannone, Asha Anoosheh, Alessio Quaglino +3
Event-based cameras are novel, efficient sensors inspired by the human vision system, generating an asynchronous, pixel-wise stream of data. Learning from such data is generally pe…
Neural Lyapunov Model Predictive Control: Learning Safe Global Controllers from Sub-optimal Examples
Mayank Mittal, Marco Gallieri, Alessio Quaglino +2
With a growing interest in data-driven control techniques, Model Predictive Control (MPC) provides an opportunity to exploit the surplus of data reliably, particularly while taking…
Infinite-Horizon Differentiable Model Predictive Control
Sebastian East, Marco Gallieri, Jonathan Masci +2
This paper proposes a differentiable linear quadratic Model Predictive Control (MPC) framework for safe imitation learning. The infinite-horizon cost is enforced using a terminal c…
Safe Interactive Model-Based Learning
Marco Gallieri, Seyed Sina Mirrazavi Salehian, Nihat Engin Toklu +4
Control applications present hard operational constraints. A violation of these can result in unsafe behavior. This paper introduces Safe Interactive Model Based Learning (SiMBL),…
Tustin neural networks: a class of recurrent nets for adaptive MPC of mechanical systems
Simone Pozzoli, Marco Gallieri, Riccardo Scattolini
The use of recurrent neural networks to represent the dynamics of unstable systems is difficult due to the need to properly initialize their internal states, which in most of the c…