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Full Bayesian identification of linear dynamic systems using stable kernels

Proceedings of the National Academy of Sciences - PNAS, 2023-05, Vol.120 (18), p.e2218197120-e2218197120

2023

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System Identification: A Machine Learning Perspective

Annual review of control, robotics, and autonomous systems, 2019-05, Vol.2 (1), p.281-304

2019

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Tracking the time course of reproduction number and lockdown’s effect on human behaviour during SARS-CoV-2 epidemic: nonparametric estimation

Scientific reports, 2021-05, Vol.11 (1), p.9772-9772, Article 9772

2021

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Full Bayesian identification of linear dynamic systems using stable kernels

Proceedings of the National Academy of Sciences - PNAS, 2023-05, Vol.120 (18)

2023

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Identification of Time-Varying Systems in Reproducing Kernel Hilbert Spaces

IEEE transactions on automatic control, 2008-10, Vol.53 (9), p.2202-2209

Pillonetto, G.

2008

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Nonlinear Stochastic Regularization to Characterize Tissue Residue Function in Bolus-Tracking MRI: Assessment and Comparison With SVD, Block-Circulant SVD, and Tikhonov

IEEE transactions on biomedical engineering, 2009-05, Vol.56 (5), p.1287-1297

2009

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Sensing, Compression, and Recovery for WSNs: Sparse Signal Modeling and Monitoring Framework

IEEE transactions on wireless communications, 2012-10, Vol.11 (10), p.3447-3461

2012

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Motion planning using adaptive random walks

IEEE transactions on robotics, 2005-02, Vol.21 (1), p.129-136

2005

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A New Kernel-Based Approach for NonlinearSystem Identification

IEEE transactions on automatic control, 2011-12, Vol.56 (12), p.2825-2840

2011

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A new dynamic index of insulin sensitivity

IEEE transactions on biomedical engineering, 2006-03, Vol.53 (3), p.369-379

2006

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Distributed parametric and nonparametric regression with on-line performance bounds computation

Automatica (Oxford), 2012-10, Vol.48 (10), p.2468-2481

2012

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Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models

2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2018, Vol.2018, p.3630-3633

2018

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Bayesian Online Multitask Learning of Gaussian Processes

IEEE transactions on pattern analysis and machine intelligence, 2010-02, Vol.32 (2), p.193-205

2010

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Client-Server Multitask Learning From Distributed Datasets

IEEE transaction on neural networks and learning systems, 2011-02, Vol.22 (2), p.290-303

2011

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Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method

IEEE transactions on biomedical engineering, 2001-11, Vol.48 (11), p.1352-1354

2001

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Numerical non-identifiability regions of the minimal model of glucose kinetics: superiority of Bayesian estimation

Mathematical biosciences, 2003-07, Vol.184 (1), p.53-67

2003

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An \ell -Laplace Robust Kalman Smoother

IEEE transactions on automatic control, 2011-12, Vol.56 (12), p.2898-2911

2011

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Estimating parameters and stochastic functions of one variable using nonlinear measurement models

Inverse problems, 2004-06, Vol.20 (3), p.627-646

2004

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On the estimation of hyperparameters for Empirical Bayes estimators: Maximum Marginal Likelihood vs Minimum MSE

IFAC Proceedings Volumes, 2012-07, Vol.45 (16), p.125-130

2012

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Approximating the Bayesian inverse for nonlinear dynamical systems

Journal of physics. Conference series, 2008-07, Vol.124 (1), p.012009

2008

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Tuning complexity in kernel-based linear system identification: The robustness of the marginal likelihood estimator

2014 European Control Conference (ECC), 2014, p.2386-2391

2014

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Minimal model S I =0 problem in NIDDM subjects: nonzero Bayesian estimates with credible confidence intervals

American journal of physiology: endocrinology and metabolism, 2002-03, Vol.282 (3), p.E564-E573

2002

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Bayesian and nonparametric methods for system identification and model selection

2014 European Control Conference (ECC), 2014, p.2376-2381

2014

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Multirobot localization with unknown variance parameters using iterated Kalman filtering

2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007, p.1709-1714

2007

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Bayesian kernel-based system identification with quantized output data

IFAC-PapersOnLine, 2015, Vol.48 (28), p.455-460

2015

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Full Bayesian identification of linear dynamic systems using stable kernels

System Identification: A Machine Learning Perspective

Tracking the time course of reproduction number and lockdown’s effect on human behaviour during SARS-CoV-2 epidemic: nonparametric estimation

Full Bayesian identification of linear dynamic systems using stable kernels

Identification of Time-Varying Systems in Reproducing Kernel Hilbert Spaces

Nonlinear Stochastic Regularization to Characterize Tissue Residue Function in Bolus-Tracking MRI: Assessment and Comparison With SVD, Block-Circulant SVD, and Tikhonov

Sensing, Compression, and Recovery for WSNs: Sparse Signal Modeling and Monitoring Framework

Motion planning using adaptive random walks

A New Kernel-Based Approach for NonlinearSystem Identification

A new dynamic index of insulin sensitivity

Distributed parametric and nonparametric regression with on-line performance bounds computation

Non-Invasive Continuous-Time Blood Pressure Estimation from a Single Channel PPG Signal using Regularized ARX Models

Bayesian Online Multitask Learning of Gaussian Processes

Client-Server Multitask Learning From Distributed Datasets

Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method

Numerical non-identifiability regions of the minimal model of glucose kinetics: superiority of Bayesian estimation

An \ell -Laplace Robust Kalman Smoother

Estimating parameters and stochastic functions of one variable using nonlinear measurement models

On the estimation of hyperparameters for Empirical Bayes estimators: Maximum Marginal Likelihood vs Minimum MSE

Approximating the Bayesian inverse for nonlinear dynamical systems

Tuning complexity in kernel-based linear system identification: The robustness of the marginal likelihood estimator

Minimal model S I =0 problem in NIDDM subjects: nonzero Bayesian estimates with credible confidence intervals

Bayesian and nonparametric methods for system identification and model selection

Multirobot localization with unknown variance parameters using iterated Kalman filtering

Bayesian kernel-based system identification with quantized output data

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