Marco Forgione

pyMPC. A Model Predictive Control (MPC) Python library based on the OSQP solver.

dynonet. "dynoNet: A neural network architecture for learning dynamical systems" by Marco Forgione and Dario Piga

sysid-neural-continuous. Continuous-time system identification with neural networks

pytorch-ident. System identification in PyTorch

efficient-calibration-embedded-MPC. Python code of the paper "Efficient Calibration of Embedded MPC" (2020 IFAC World Congress) by Marco Forgione, Dario Piga, and Alberto Bemporad

sysid-transfer-functions-pytorch. Codes accompanying the paper "Deep learning with transfer functions: new applications in system identification"

sysid-neural-structures-fitting. Python code of the paper "Model structures and fitting criteria for system identification with neural networks" by Marco Forgione and Dario Piga.

sysid-transformers. Code to reproduce the results of the paper In-context learning for model-free system identification

dl-sysid-eeci2025. Jupyter Notebook

dl-sysid-lyon2026. Material for the mini-course on Deep Learning for System Identification (Lyon 2026)

lru-reduction. Python code of the paper Model order reduction of deep structured state-space models: A system-theoretic approach

RNN-adaptation. Code accompanying the paper "On the adaptation of recurrent neural networks for system identification"

sysid-neural-estimator. Code accompanying the paper "Learning neural state-space models: do we need a state estimator?"

jax-tutorial. JAX tutorial for people already familiar with PyTorch

sysid-neural-unc. Code of the paper "Neural state-space models: Empirical evaluation of uncertainty quantification"

sysid-neural-manifold. Code accompanying the paper "Manifold meta-learning for reduced-complexity neural system identification"

sysid-transformers-transfer. Code of the paper "On the adaptation of in-context learners for system identification" by Dario Piga, Filippo Pura, and Marco Forgione

jax-ident. An experimental code base for system identification with Jax.

sysid-pytorch-lru. Unofficial PyTorch implementation of DeepMind's LRU with a system identification example.

python-data-science-slides. An introduction to data processing & visualization with numpy, pandas, matplotlib, and plotly express

control-theory-in-lean. Formalization of foundational Control Theory in Lean (early attempts)

bayesian-optimization-examples. Bayesian Optimization examples

jax-sysid. A Python package for linear subspace identification, nonlinear system identification, and nonlinear regression using Jax

multilevel-excitation. Codes accompanying the paper "Experiment design for parameter estimation in nonlinear systems based on multilevel excitation"

pytorch-meta-learning. Minimal documented meta learning implementations in PyTorch

calcolo_mutuo. Python