16 citations · 16 across the 2 of their papers we have counts for
10 papers
Variational meta-learning inference for low dimensional neural system identification
Matteo Rufolo, Dario Piga, Marco Forgione
Deep learning has proven highly effective for nonlinear system identification, but heavily parameterized neural networks are prone to overfitting in low-data regimes and lack relia…
From system models to class models: An in-context learning paradigm
Marco Forgione, Filippo Pura, Dario Piga
Is it possible to understand the intricacies of a dynamical system not solely from its input/output pattern, but also by observing the behavior of other systems within the same cla…
ASIA: an Autonomous System Identification Agent
Dario Piga, Marco Forgione
Over the years, research in system identification has provided a rich set of methods for learning dynamical models, together with well-established theoretical guarantees. In practi…
Nonlinear System Identification Nano-drone Benchmark
Riccardo Busetto, Elia Cereda, Marco Forgione +3
We introduce a benchmark for system identification based on 75k real-world samples from the Crazyflie 2.1 Brushless nano-quadrotor, a sub-50g aerial vehicle widely adopted in robot…
Learning Low-Dimensional Embeddings for Black-Box Optimization
Riccardo Busetto, Manas Mejari, Marco Forgione +2
When gradient-based methods are impractical, black-box optimization (BBO) provides a valuable alternative. However, BBO often struggles with high-dimensional problems and limited t…
The Duality of Generative AI and Reinforcement Learning in Robotics: A Review
Angelo Moroncelli, Vishal Soni, Marco Forgione +3
Recently, generative AI and reinforcement learning (RL) have been redefining what is possible for AI agents that take information flows as input and produce intelligent behavior. A…