Thomas Schön

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Fredrik LindstenAssociate Professor, Linköping UniversityPatvirtintas el. paštas liu.se
Fredrik GustafssonProf, Linköping University, SwedenPatvirtintas el. paštas liu.se
Adrian WillsUniversity of Newcastle AustraliaPatvirtintas el. paštas newcastle.edu.au
Manon KokAssociate Professor at the Delft Center for Systems and ControlPatvirtintas el. paštas tudelft.nl
Jeroen D. HolSnapPatvirtintas el. paštas snap.com
Niklas WahlströmAssociate Professor, Uppsala University, SwedenPatvirtintas el. paštas it.uu.se
B NinnessUniversity of Newcastle AustraliaPatvirtintas el. paštas newcastle.edu.au
Andreas Lindholm (Svensson)Machine Learning Research Engineer, KognicPatvirtintas el. paštas kognic.com
Fredrik K. GustafssonPostdoctoral Researcher, Karolinska InstitutetPatvirtintas el. paštas ki.se
Antônio H. RibeiroAssistant Professor, Uppsala UniversityPatvirtintas el. paštas it.uu.se
Johan DahlinKotte Consulting AB, Stockholm, SwedenPatvirtintas el. paštas johandahlin.com
Lennart LjungProfessor of Automatic Control, Linköping University, SwedenPatvirtintas el. paštas isy.liu.se
Carl AnderssonUppsala UniversityPatvirtintas el. paštas it.uu.se
Jens SjölundAssistant Professor at Uppsala UniversityPatvirtintas el. paštas it.uu.se
Carl JidlingUppsala UniversityPatvirtintas el. paštas it.uu.se
Antonio Luiz P. RibeiroUniversidade Federal de Minas Gerais, BrasilPatvirtintas el. paštas hc.ufmg.br
Wagner Meira, Jr.Professor of Computer Science, Universidade Federal de Minas Gerais, BrazilPatvirtintas el. paštas dcc.ufmg.br
Rickard KarlssonAutomatic Control, Linköping University, Linköping, SwedenPatvirtintas el. paštas isy.liu.se
Daniel GedonPostdoctoral Fellow, Tübingen UniversityPatvirtintas el. paštas uni-tuebingen.de
Derick M. OliveiraUniversidade Federal de Minas GeraisPatvirtintas el. paštas dcc.ufmg.br

Stebėti

Thomas Schön

Professor, Uppsala University

Patvirtintas el. paštas it.uu.se - Pagrindinis puslapis

Machine Learning Artificial intelligence Monte Carlo methods Gaussian processes System Identification


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Marginalized particle filters for mixed linear/nonlinear state-space models T Schön, F Gustafsson, PJ Nordlund IEEE Transactions on Signal Processing 53 (7), 2279-2289, 2005	925	2005
Automatic diagnosis of the 12-lead ECG using a deep neural network AH Ribeiro, MH Ribeiro, GMM Paixão, DM Oliveira, PR Gomes, ... Nature Communications 11 (1760), 2020	863	2020
Using inertial sensors for position and orientation estimation M Kok, JD Hol, TB Schön Foundations and Trends in Signal Processing 11 (1-2), 1-153, 2017	754	2017
System identification of nonlinear state-space models TB Schön, A Wills, B Ninness Automatica 47 (1), 39-49, 2011	686	2011
On resampling algorithms for particle filters JD Hol, TB Schön, F Gustafsson IEEE Nonlinear Statistical Signal Processing Workshop, 2006	641	2006
Identification of Hammerstein–Wiener models A Wills, TB Schön, L Ljung, B Ninness Automatica 49 (1), 70-81, 2013	393	2013
Evaluating scalable bayesian deep learning methods for robust computer vision FK Gustafsson, M Danelljan, TB Schön Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020	355	2020
The eighth visual object tracking VOT2020 challenge results M Kristan, A Leonardis, J Matas, M Felsberg, R Pflugfelder, ... European Conference on Computer Vision (ECCV), 547-601, 2020	353	2020
Particle Gibbs with Ancestor Sampling F Lindsten, MI Jordan, TB Schön Journal of Machine Learning Research 15, 2145-2184, 2014	351	2014
Evaluating model calibration in classification J Vaicenavicius, D Widmann, C Andersson, F Lindsten, J Roll, TB Schön International Conference on Artificial Intelligence and Statistics (AISTATS …, 2019	265	2019
Indoor positioning using ultrawideband and inertial measurements M Kok, JD Hol, TB Schön IEEE Transactions on Vehicular Technology 64 (4), 1293-1303, 2015	247	2015
Machine Learning: A First Course for Engineers and Scientists A Lindholm, N Wahlström, F Lindsten, TB Schön Cambridge University Press, 2022	243	2022
From pixels to torques: Policy learning with deep dynamical models N Wahlström, TB Schön, MP Deisenroth International Conference on Machine Learning (ICML) - Deep Learning Workshop, 2015	237	2015
Complexity analysis of the marginalized particle filter R Karlsson, T Schön, F Gustafsson IEEE Transactions on Signal Processing 53 (11), 4408-4411, 2005	226	2005
Magnetometer calibration using inertial sensors M Kok, TB Schön IEEE Sensors Journal 16 (14), 5679-5689, 2016	220	2016
Backward simulation methods for Monte Carlo statistical inference F Lindsten, TB Schön Foundations and Trends in Machine Learning 6 (1), 1-143, 2013	203	2013
A basic convergence result for particle filtering XL Hu, TB Schön, L Ljung IEEE Transactions on Signal Processing 56 (4), 1337-1348, 2008	203	2008
Tightly coupled UWB/IMU pose estimation J Hol, F Dijkstra, H Luinge, TB Schön Proceedings of the IEEE International Conference on Ultra-Wideband (ICUWB …, 2009	202	2009
Deep learning and system identification L Ljung, C Andersson, K Tiels, TB Schön IFAC-PapersOnLine 53 (2), 1175-1181, 2020	194	2020
Bayesian inference and learning in Gaussian process state-space models with particle MCMC R Frigola, F Lindsten, TB Schön, CE Rasmussen Advances in Neural Information Processing Systems (NIPS), 3156-3164, 2013	181	2013

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