Giulio Bottegal

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Håkan HjalmarssonCentre for Advanced Bioproduction, Linnaeus Centre ACCESS, School of EE and CSCorreu electrònic verificat a kth.se
Gianluigi PillonettoProfessor of Automatic Control, University of PadovaCorreu electrònic verificat a dei.unipd.it
Karl H. JohanssonEECS and Digital Futures, KTH Royal Institute of Technology, SwedenCorreu electrònic verificat a kth.se
Paul M.J. Van den HofProfessor Eindhoven University of TechnologyCorreu electrònic verificat a tue.nl
Damiano VaragnoloDepartment of Engineering Cybernetics, NTNU - Norwegian University of Science and TechnologyCorreu electrònic verificat a ntnu.no
Bo WahlbergProfessor Automatic Control, KTH Royal Institute of TechnologyCorreu electrònic verificat a kth.se
Afrooz EbadatKTH Royal Institute of TechnologyCorreu electrònic verificat a kth.se
Niklas EverittPhd-studentCorreu electrònic verificat a kth.se
Giorgio PicciProfessore Emerito, Dipartimento di Ingegneria dell'Informazione, Universita` di PadovaCorreu electrònic verificat a dei.unipd.it
Aleksandr AravkinUniversity of WashingtonCorreu electrònic verificat a uw.edu
Karthik Raghavan RamaswamyPhD (cum laude), Eindhoven University of TechnologyCorreu electrònic verificat a tue.nl
Cristian R. RojasProfessor, Division of Decision and Control Systems, KTH Royal Institute of TechnologyCorreu electrònic verificat a kth.se
Johan SuykensProfessor, KU LeuvenCorreu electrònic verificat a esat.kuleuven.be
Mohsen ZamaniUniversity of NewcastleCorreu electrònic verificat a newcastle.edu.au
Brian AndersonAustralian National University, Hangzhou Dianzi University, Data61-CSIROCorreu electrònic verificat a anu.edu.au
Shengling ShiDelft University of TechnologyCorreu electrònic verificat a tudelft.nl
Miguel GalrinhoKTH Royal Institute of TechnologyCorreu electrònic verificat a kth.se
Harm WeertsDoctoral candidate (PhD) at Control Systems, Eindhoven University of TechnologyCorreu electrònic verificat a tue.nl
Iman ShamesAustralian National UniversityCorreu electrònic verificat a anu.edu.au
Farhad FarokhiThe University of Melbourne, AustraliaCorreu electrònic verificat a unimelb.edu.au

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Giulio Bottegal

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System Identification Machine Learning Control Systems


Títol Ordena per cites Ordena per any Ordena per títol	Citada per Citada per	Any
Estimation of building occupancy levels through environmental signals deconvolution A Ebadat, G Bottegal, D Varagnolo, B Wahlberg, KH Johansson Proceedings of the 5th ACM Workshop on Embedded Systems For Energy-Efficient …, 2013	85	2013
Robust EM kernel-based methods for linear system identification G Bottegal, AY Aravkin, H Hjalmarsson, G Pillonetto Automatica 67, 114-126, 2016	51	2016
Regularized deconvolution-based approaches for estimating room occupancies A Ebadat, G Bottegal, D Varagnolo, B Wahlberg, KH Johansson IEEE Transactions on Automation Science and Engineering 12 (4), 1157-1168, 2015	45	2015
An empirical Bayes approach to identification of modules in dynamic networks N Everitt, G Bottegal, H Hjalmarsson Automatica 91, 144-151, 2018	43	2018
A nonparametric kernel-based approach to Hammerstein system identification RS Risuleo, G Bottegal, H Hjalmarsson Automatica 85, 234-247, 2017	40	2017
A new kernel-based approach to system identification with quantized output data G Bottegal, H Hjalmarsson, G Pillonetto Automatica 85, 145-152, 2017	38	2017
Local module identification in dynamic networks using regularized kernel-based methods KR Ramaswamy, G Bottegal, PMJ Van den Hof 2018 IEEE Conference on Decision and Control (CDC), 4713-4718, 2018	31	2018
Regularized spectrum estimation using stable spline kernels G Bottegal, G Pillonetto Automatica 49 (11), 3199-3209, 2013	22	2013
A kernel-based approach to Hammerstein system identification RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 48 (28), 1011-1016, 2015	21	2015
Local module identification in dynamic networks with correlated noise: the full input case PMJ Van den Hof, KR Ramaswamy, AG Dankers, G Bottegal 2019 IEEE 58th Conference on Decision and Control (CDC), 5494-5499, 2019	20	2019
A two-experiment approach to Wiener system identification G Bottegal, R Castro-Garcia, JAK Suykens Automatica 93, 282-289, 2018	20	2018
Bayesian topology identification of linear dynamic networks S Shi, G Bottegal, PMJ Van den Hof 2019 18th European Control Conference (ECC), 2814-2819, 2019	19	2019
Blind identification strategies for room occupancy estimation A Ebadat, G Bottegal, D Varagnolo, B Wahlberg, H Hjalmarsson, ... 2015 European control conference (ECC), 1315-1320, 2015	19	2015
Learning linear modules in a dynamic network using regularized kernel-based methods KR Ramaswamy, G Bottegal, PMJ Van den Hof Automatica 129, 109591, 2021	18	2021
Blind system identification using kernel-based methods G Bottegal, RS Risuleo, H Hjalmarsson IFAC-PapersOnLine 48 (28), 466-471, 2015	18	2015
Modeling complex systems by generalized factor analysis G Bottegal, G Picci IEEE Transactions on Automatic Control 60 (3), 759-774, 2014	18	2014
Outlier robust system identification: A Bayesian kernel-based approach G Bottegal, AY Aravkin, H Hjalmarsson, G Pillonetto IFAC Proceedings Volumes 47 (3), 1073-1078, 2014	16	2014
Identification of linear models from quantized data: a midpoint-projection approach RS Risuleo, G Bottegal, H Hjalmarsson IEEE Transactions on Automatic Control 65 (7), 2801-2813, 2019	13	2019
A sequential least squares algorithm for ARMAX dynamic network identification HHM Weerts, M Galrinho, G Bottegal, H Hjalmarsson, PMJ Van den Hof IFAC-PapersOnLine 51 (15), 844-849, 2018	13	2018
Multi-room occupancy estimation through adaptive gray-box models A Ebadat, G Bottegal, M Molinari, D Varagnolo, B Wahlberg, ... Decision and Control (CDC), 2015 IEEE 54th Annual Conference on, 3705 - 3711, 2015	13	2015

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