4 papers
Statistical Parameter Calibration via the Generalized Fluctuation Dissipation Theorem and Generative Modeling
Ludovico T. Giorgini, Tobias Bischoff, Andre N. Souza
We introduce a response-theoretic framework that recasts parameter calibration of ergodic stochastic differential equations as a fluctuation-dissipation problem. Our central result…
KGMM: A K-means Clustering Approach to Gaussian Mixture Modeling for Score Function Estimation
Ludovico T. Giorgini, Tobias Bischoff, Andre N. Souza
We propose a hybrid method for accurately estimating the score function, i.e., the gradient of the log steady-state density, using a Gaussian Mixture Model (GMM) in conjunction wit…
Predicting Forced Responses of Probability Distributions via the Fluctuation-Dissipation Theorem and Generative Modeling
Ludovico T. Giorgini, Fabrizio Falasca, Andre N. Souza
We present a novel and flexible data-driven framework for estimating the response of higher-order moments of nonlinear stochastic systems to small external perturbations. The class…
Learning dissipation and instability fields from chaotic dynamics
Ludovico T Giorgini, Andre N Souza, Domenico Lippolis +2
To make predictions or design control, information on local sensitivity of initial conditions and state-space contraction is both central, and often instrumental. However, it is no…