Ludovico Theo Giorgini

Publications

G. Del Felice and L.T. Giorgini, Integrating Score-Based Generative Modeling and Neural ODEs for Accurate Representation of Multiscale Chaotic Dynamics, arXiv preprint arXiv:2511.03862 (2025).
L.T. Giorgini, T. Bischoff, A. Souza, Statistical Parameter Calibration with the Generalized Fluctuation Dissipation Theorem and Generative Modeling, arXiv preprint arXiv:2509.19660 (2025).
L.T. Giorgini, T. Bischoff, A. Souza, Reduced-Order Modeling of Cyclo-Stationary Time Series Using Score-Based Generative Methods, arXiv preprint arXiv:2508.19448 (2025).
L.T. Giorgini, Data-Driven Decomposition of Conservative and Non-Conservative Dynamics in Multiscale Systems, arXiv preprint arXiv:2505.01895 (2025).
L.T. Giorgini, F. Falasca, and A. Souza, Predicting forced responses of probability distributions via the fluctuation-dissipation theorem and generative modeling, Proc. Natl. Acad. Sci. U. S. A., 122, e2509578122 (2025).
L.T. Giorgini, T. Bischoff, A. Souza, KGMM: A K-means Clustering Approach to Gaussian Mixture Modeling for Score Function Estimation, arXiv preprint arXiv:2503.18054 (2025).
L.T. Giorgini, A. Souza, D. Lippolis, P. Cvitanović and P. Schmid, Learning dissipation and instability fields from chaotic dynamics, Physica D: Nonlinear Phenomena, 481, 134865 (2025).
L.T. Giorgini, K. Deck, T. Bischoff, A. Souza, Response Theory via Generative Score Modeling, Phys. Rev. Lett., 133, 267302 (2024).
L.T. Giorgini, A. Souza and P. Schmid, Reduced Markovian Models of Dynamical Systems, Physica D: Nonlinear Phenomena, 470, 134393 (2024).
L.T. Giorgini et al., Instantons in ϕ⁴ Theories: Transseries, Virial Theorems and Numerical Aspects, Phys. Rev. D, 110, 036003 (2024) (Editor's choice).
L.T. Giorgini, W. Moon, and J.S. Wettlaufer, Analytical Survival Analysis of the Non-autonomous Ornstein-Uhlenbeck Process, J. Stat. Phys., 191, 138 (2024).
U.D. Jentschura, L.T. Giorgini, Enhanced One-Step Neville Algorithm with Access to the Convergence Rate, Comp. Phys. Comm. 109280 (2024).
N. Keyes, L.T. Giorgini and J.S. Wettlaufer, Stochastic Paleoclimatology: Modeling the EPICA Ice Core Climate Records, Chaos, 33, 093132 (2023).
L.T. Giorgini, R. Eichorn, M. Das, W. Moon and J.S. Wettlaufer, The Thermodynamic Cost of Erasing Information in Finite-time, Phys. Rev. Res., 5, 023084 (2023).
L.T. Giorgini, U.D. Jentschura, E.M. Malatesta, G. Parisi, T. Rizzo, and J. Zinn-Justin, Correlation Functions of the Anharmonic Oscillator: Numerical Verification of Two-Loop Corrections to the Large-Order Behavior, Phys. Rev. D, 105, 105012 (2022).
L.T. Giorgini, W. Moon, N. Chen and J.S. Wettlaufer, A Non-Gaussian Stochastic Model for the El Niño Southern Oscillation, Phys. Rev. Res., 4, L022065 (2022).
L.T. Giorgini, W. Moon, N. Chen and J.S. Wettlaufer, Modeling the El Niño Southern Oscillation with Neural Differential Equations, TSM-ICML (2021).
W. Moon, L.T. Giorgini, and J.S. Wettlaufer, Nonadiabatic stochastic resonance: An analytical solution, Phys. Rev. E, 104, 044130 (2021).
S.H. Lim, L.T. Giorgini, W. Moon, and J.S. Wettlaufer, Predicting rare events in multiscale dynamical systems using machine learning, Chaos, 30, 123126 (2020).
L.T. Giorgini, U.D. Jentschura, E.M. Malatesta, G. Parisi, T. Rizzo, and J. Zinn-Justin, Two-loop corrections to the large-order behavior of correlation functions in the one-dimensional N-vector model, Phys. Rev. D, 101, 125001 (2020).
L.T. Giorgini, W. Moon, and J.S. Wettlaufer, Analytical Survival Analysis of the Ornstein–Uhlenbeck Process, J. Stat. Phys., 181, 2404 (2020).
L.T. Giorgini, S.H. Lim, W. Moon, and J.S. Wettlaufer, Precursors to rare events in stochastic resonance, EPL, 129, 40003 (2020) (Editor's choice).

Open-Source Software

DiscreteTransformers.jl

Julia package for time-series forecasting with transformers on discretized state spaces; clusters continuous signals into symbols and learns transition dynamics for ensemble forecasting and scenario generation.

ContinuousTransformers.jl

Transformers operating directly on continuous, delay-embedded sequences for next-step prediction, probabilistic ensembles, and compact representations.

FastSDE.jl

Speed-first Julia library for simulating stochastic/deterministic dynamical systems (additive/diagonal/correlated noise, StaticArrays fast path, multithreading).

ScoreEstimation.jl

KGMM-based score estimation: bisecting k-means + Gaussian mixture modeling with neural interpolation to build robust local score fields in high-dimensional dynamics.

ParameterCalibration.jl

GFDT-based parameter calibration toolkit: computes Jacobians of statistical observables from a single baseline run; supports drift/diffusion parameters with worked examples.

ScoreUNet1D.jl

Julia package that trains a 1D U-Net via denoising score matching and validates its learned score by running Langevin SDE on the Kuramoto–Sivashinsky system.

About Me