3 citations · 4 across the 7 of their papers we have counts for
7 papers
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…
Enhanced Transformer architecture for in-context learning of dynamical systems
Matteo Rufolo, Dario Piga, Gabriele Maroni +1
Recently introduced by some of the authors, the in-context identification paradigm aims at estimating, offline and based on synthetic data, a meta-model that describes the behavior…
LightCPPgen: An Explainable Machine Learning Pipeline for Rational Design of Cell Penetrating Peptides
Gabriele Maroni, Filip Stojceski, Lorenzo Pallante +3
Cell-penetrating peptides (CPPs) are powerful vectors for the intracellular delivery of a diverse array of therapeutic molecules. Despite their potential, the rational design of CP…
Synthetic data generation for system identification: leveraging knowledge transfer from similar systems
Dario Piga, Matteo Rufolo, Gabriele Maroni +2
This paper addresses the challenge of overfitting in the learning of dynamical systems by introducing a novel approach for the generation of synthetic data, aimed at enhancing mode…
Gradient-based bilevel optimization for multi-penalty Ridge regression through matrix differential calculus
Gabriele Maroni, Loris Cannelli, Dario Piga
Common regularization algorithms for linear regression, such as LASSO and Ridge regression, rely on a regularization hyperparameter that balances the tradeoff between minimizing th…
Split-Boost Neural Networks
Raffaele Giuseppe Cestari, Gabriele Maroni, Loris Cannelli +2
The calibration and training of a neural network is a complex and time-consuming procedure that requires significant computational resources to achieve satisfactory results. Key ob…
Electricity Load and Peak Forecasting: Feature Engineering, Probabilistic LightGBM and Temporal Hierarchies
Nicolò Rubattu, Gabriele Maroni, Giorgio Corani
We describe our experience in developing a predictive model that placed high position in the BigDeal Challenge 2022, an energy competition of load and peak forecasting. We present…