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06/06/2021
A novel Deep Neural Network architecture for non-linear system identification
We present a novel Deep Neural Network (DNN) architecture for non-linear...
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03/25/2021
Estimating Koopman operators for nonlinear dynamical systems: a nonparametric approach
The Koopman operator is a mathematical tool that allows for a linear des...
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09/13/2018
Derivative-free online learning of inverse dynamics models
This paper discusses online algorithms for inverse dynamics modelling in...
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03/17/2016
Online semi-parametric learning for inverse dynamics modeling
This paper presents a semi-parametric algorithm for online learning of a...
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01/17/2016
On-line Bayesian System Identification
We consider an on-line system identification setting, in which new data ...
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08/12/2015
Maximum Entropy Vector Kernels for MIMO system identification
Recent contributions have framed linear system identification as a nonpa...
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07/02/2015
Identification of stable models via nonparametric prediction error methods
A new Bayesian approach to linear system identification has been propose...
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03/25/2015
A Bayesian Approach to Sparse plus Low rank Network Identification
We consider the problem of modeling multivariate time series with parsim...
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11/27/2014
Visual Representations: Defining Properties and Deep Approximations
Visual representations are defined in terms of minimal sufficient statis...
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09/29/2014
Bayesian and regularization approaches to multivariable linear system identification: the role of rank penalties
Recent developments in linear system identification have proposed the us...
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06/25/2014
A scaled gradient projection method for Bayesian learning in dynamical systems
A crucial task in system identification problems is the selection of the...
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02/26/2013