A nonparametric kernel-based approach to Hammerstein system identification RS Risuleo, G Bottegal, H Hjalmarsson Automatica 85, 234-247, 2017 | 46 | 2017 |
Bayesian nonparametric identification of Wiener systems RS Risuleo, F Lindsten, H Hjalmarsson Automatica 108, 108480, 2019 | 25 | 2019 |
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 | 25 | 2019 |
A kernel-based approach to Hammerstein system identification RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 48 (28), 1011-1016, 2015 | 23 | 2015 |
Parameter elimination in particle Gibbs sampling A Wigren, RS Risuleo, L Murray, F Lindsten Advances in Neural Information Processing Systems 32, 2019 | 20 | 2019 |
Blind system identification using kernel-based methods G Bottegal, RS Risuleo, H Hjalmarsson IFAC-PapersOnLine 48 (28), 466-471, 2015 | 19 | 2015 |
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 | 17 | 2020 |
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 | 15 | 2017 |
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 | 15 | 2015 |
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 | 13 | 2015 |
The klarna product page dataset: A realistic benchmark for web representation learning A Hotti, RS Risuleo, S Magureanu, A Moradi, J Lagergren arXiv preprint arXiv:2111.02168, 2021 | 12 | 2021 |
System identification with input uncertainties: an EM kernel-based approach RS Risuleo KTH Royal Institute of Technology, 2016 | 12 | 2016 |
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 | 11 | 2016 |
Modeling and identification of uncertain-input systems RS Risuleo, G Bottegal, H Hjalmarsson Automatica 105, 130-141, 2019 | 10 | 2019 |
Variational Bayes identification of acyclic dynamic networks RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 50 (1), 10556-10561, 2017 | 7 | 2017 |
Approximate maximum-likelihood identification of linear systems from quantized measurements RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 51 (15), 724-729, 2018 | 6 | 2018 |
Approximate inference of nonparametric Hammerstein models RS Risuleo, G Bottegal, H Hjalmarsson IFAC-PapersOnLine 50 (1), 8333-8338, 2017 | 5 | 2017 |
Graph neural networks for nomination and representation learning of web elements A Hotti, RS Risuleo, S Magureanu, A Moradi, J Lagergren arXiv preprint arXiv:2111.02168, 2021 | 4 | 2021 |
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 | 4 | 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 | 4 | 2015 |