| A nonparametric kernel-based approach to Hammerstein system identification RS Risuleo, G Bottegal, H Hjalmarsson Automatica 85, 234-247, 2017 | 15 | 2017 |
| A kernel-based approach to Hammerstein system identification RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 48 (28), 1011-1016, 2015 | 15 | 2015 |
| Blind system identification using kernel-based methods G Bottegal, RS Risuleo, H Hjalmarsson IFAC-PapersOnLine 48 (28), 466-471, 2015 | 13 | 2015 |
| System identification with input uncertainties: an EM kernel-based approach RS Risuleo KTH Royal Institute of Technology, 2016 | 10 | 2016 |
| A benchmark for data-based office modeling: challenges related to CO2 dynamics RS Risuleo, M Molinari, G Bottegal, H Hjalmarsson, KH Johansson IFAC-PapersOnLine 48 (28), 1256-1261, 2015 | 10 | 2015 |
| Optimal power control for D2D communications under Rician fading: A risk theoretical approach D Della Penda, RS Risuleo, PE Valenzuela, M Johansson GLOBECOM 2017-2017 IEEE Global Communications Conference, 1-6, 2017 | 9 | 2017 |
| Kernel-based system identification from noisy and incomplete input-output data RS Risuleo, G Bottegal, H Hjalmarsson 2016 IEEE 55th Conference on Decision and Control (CDC), 2061-2066, 2016 | 8 | 2016 |
| A new kernel-based approach to overparameterized Hammerstein system identification RS Risuleo, G Bottegal, H Hjalmarsson 2015 54th IEEE Conference on Decision and Control (CDC), 115-120, 2015 | 8 | 2015 |
| Modeling and identification of uncertain-input systems RS Risuleo, G Bottegal, H Hjalmarsson Automatica 105, 130-141, 2019 | 4 | 2019 |
| Parameter elimination in particle Gibbs sampling A Wigren, RS Risuleo, L Murray, F Lindsten Advances in Neural Information Processing Systems, 8918-8929, 2019 | 4 | 2019 |
| Approximate inference of nonparametric Hammerstein models RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 50 (1), 8333-8338, 2017 | 4 | 2017 |
| Variational Bayes identification of acyclic dynamic networks RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 50 (1), 10556-10561, 2017 | 4 | 2017 |
| Bayesian nonparametric identification of Wiener systems RS Risuleo, F Lindsten, H Hjalmarsson Automatica 108, 108480, 2019 | 3 | 2019 |
| On maximum likelihood identification of errors-in-variables models G Bottegal, RS Risuleo, M Zamani, B Ninness, H Hjalmarsson IFAC-PapersOnLine 50 (1), 2824-2829, 2017 | 3 | 2017 |
| Identification of nonlinear kinetics of macroscopic bio-reactions using multilinear Gaussian processes M Wang, RS Risuleo, EW Jacobsen, V Chotteau, H Hjalmarsson Computers & Chemical Engineering 133, 106671, 2020 | 1 | 2020 |
| Identification of linear models from quantized data: a midpoint-projection approach RS Risuleo, G Bottegal, H Hjalmarsson IEEE Transactions on Automatic Control, 2019 | 1 | 2019 |
| Semi-parametric kernel-based identification of Wiener systems RS Risuleo, F Lindsten, H Hjalmarsson 2018 IEEE Conference on Decision and Control (CDC), 3874-3879, 2018 | 1 | 2018 |
| Outlier-Robust Estimation of Uncertain-Input Systems With Applications to Nonparametric FIR and Hammerstein Models RS Risuleo, H Hjalmarsson IEEE control systems letters 2 (4), 647-652, 2018 | 1 | 2018 |
| Approximate maximum-likelihood identification of linear systems from quantized measurements RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 51 (15), 724-729, 2018 | 1 | 2018 |
| On the estimation of initial conditions in kernel-based system identification RS Risuleo, G Bottegal, H Hjalmarsson 2015 54th IEEE Conference on Decision and Control (CDC), 1120-1125, 2015 | 1 | 2015 |
Håkan HjalmarssonCentre for Advanced Bioproduction, Linnaeus Centre ACCESS, School of EE and CSVerified email at ee.kth.se
