Publications related to Quotient-method Algorithms for Input-affine Single-input Nonlinear Systems

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

Alfio Quarteroni, Francesco Regazzoni, Stefano Pagani

Predicting the evolution of systems with spatio-temporal dynamics in response to external stimuli is essential for scientific progress. Traditional equations-based approaches leverage first principles through the numerical approximation of differential equ ...

Nature Portfolio2024

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

Fabio Nobile, Tommaso Vanzan

We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of optimal control problems (OCPs) constrained by random partial differential equ ...

2024

A Proximal-Point Lagrangian-Based Parallelizable Nonconvex Solver for Bilinear Model Predictive Control

Colin Neil Jones, Yuning Jiang, Yingzhao Lian

Nonlinear model predictive control (NMPC) has been widely adopted to manipulate bilinear systems with dynamics that include products of the inputs and the states. These systems are ubiquitous in chemical processes, mechanical systems, and quantum physics, ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Learning Linearized Degradation of Health Indicators using Deep Koopman Operator Approach

Olga Fink, Sergei Garmaev

With the current trend of increasing complexity of industrial systems, the construction and monitoring of health indicators becomes even more challenging. Given that health indicators are commonly employed to predict the end of life, a crucial criterion fo ...

Research Publishing2023

Fast in vivo assay of creatine kinase activity in the human brain by P-31 magnetic resonance fingerprinting

Lijing Xin, Daniel Wenz, Mark Stephan Widmaier, Songi Lim

A new and efficient magnetisation transfer P-31 magnetic resonance fingerprinting (MT-P-31-MRF) approach is introduced to measure the creatine kinase metabolic rate kCK

{k}_{\mathrm{CK}}

between phosphocreatine (PCr) and adenosine triphosphate (ATP) i ...

WILEY2023

A combination technique for optimal control problems constrained by random PDEs

Fabio Nobile, Tommaso Vanzan

We present a combination technique based on mixed differences of both spatial approximations and quadrature formulae for the stochastic variables to solve efficiently a class of Optimal Control Problems (OCPs) constrained by random partial differential equ ...

EPFL2022

Information-driven transitions in projections of underdamped dynamics

Daniel Maria Busiello, Giorgio Nicoletti, Amos Maritan

Low-dimensional representations of underdamped systems often provide useful insights and analytical tractability. Here, we build such representations via information projections, obtaining an optimal model that captures the most information on observed spa ...

AMER PHYSICAL SOC2022

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Giacomo Garegnani

In this thesis we explore uncertainty quantification of forward and inverse problems involving differential equations. Differential equations are widely employed for modeling natural and social phenomena, with applications in engineering, chemistry, meteor ...

EPFL2021

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Fabio Nobile, Sebastian Krumscheid, Matthieu Claude Martin

We consider the numerical approximation of an optimal control problem for an elliptic Partial Differential Equation (PDE) with random coefficients. Specifically, the control function is a deterministic, distributed forcing term that minimizes the expected ...

2021

On the optimal controllability time for linear hyperbolic systems with time-dependent coefficients

Hoài-Minh Nguyên

The optimal time for the controllability of linear hyperbolic systems in one dimensional space with one-side controls has been obtained recently for time-independent coefficients in our previous works. In this paper, we consider linear hyperbolic systems w ...

2021

Quotient-method Algorithms for Input-affine Single-input Nonlinear Systems

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Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

A Proximal-Point Lagrangian-Based Parallelizable Nonconvex Solver for Bilinear Model Predictive Control

Learning Linearized Degradation of Health Indicators using Deep Koopman Operator Approach

Fast in vivo assay of creatine kinase activity in the human brain by P-31 magnetic resonance fingerprinting

A combination technique for optimal control problems constrained by random PDEs

Information-driven transitions in projections of underdamped dynamics

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

On the optimal controllability time for linear hyperbolic systems with time-dependent coefficients

Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks

A Combination Technique for Optimal Control Problems Constrained by Random PDEs

Complexity analysis of stochastic gradient methods for PDE-constrained optimal control problems with uncertain parameters

Information-driven transitions in projections of underdamped dynamics

Fast in vivo assay of creatine kinase activity in the human brain by P-31 magnetic resonance fingerprinting

A Proximal-Point Lagrangian-Based Parallelizable Nonconvex Solver for Bilinear Model Predictive Control

Probabilistic and Bayesian methods for uncertainty quantification of deterministic and stochastic differential equations

On the optimal controllability time for linear hyperbolic systems with time-dependent coefficients

A combination technique for optimal control problems constrained by random PDEs

Learning Linearized Degradation of Health Indicators using Deep Koopman Operator Approach