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Janne M. J. Huttunen

Observed names: HUTTUNEN, JANNE, Huttunen, Janne, Huttunen, Janne M J, Huttunen, Janne M. J., Huttunen, Janne M.J., Huttunen, Janne MJ, J M J Huttunen, J. M. J. Huttunen, J.M.J. Huttunen, Janne Huttunen, Janne M J Huttunen, Janne M.J. Huttunen, Janne M. J. Huttunen
Institution: Nokia (Finland)
Observed institutions: University of Auckland, University of Eastern Finland, Nokia (Finland), Eastern Finland Laboratory Center, Kainuun keskussairaala, University of California, Berkeley
ORCID: 0000-0002-4549-0272
Observed ORCID: 0000-0002-4549-0272
OpenAlex ID: A5065186178
DeepRx: Fully Convolutional Deep Learning Receiver
2021 · Mikko Honkala, Dani Korpi, et al. · IEEE Transactions on Wireless Communications · 235
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Whittle-Matérn priors for Bayesian statistical inversion with applications in electrical impedance tomography
2014 · Lassi Roininen, Janne M. J. Huttunen, et al. · Inverse Problems and Imaging · 138
Approximation errors in nonstationary inverse problems
2007 · Janne M.J. Huttunen, J. P. Kaipio · Inverse Problems and Imaging · 56
Pulse transit time estimation of aortic pulse wave velocity and blood pressure using machine learning and simulated training data
2019 · Janne M. J. Huttunen, Leo Kärkkäinen, et al. · PLoS Computational Biology · 53
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Experimental evaluation of 3D electrical impedance tomography with total variation prior
2015 · G. González, J. M. J. Huttunen, et al. · Inverse Problems in Science and Engineering · 53
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MRI contrasts in high rank rotating frames
2014 · Timo Liimatainen, Hanne Hakkarainen, et al. · Magnetic Resonance in Medicine · 53
Dynamic inversion for hydrological process monitoring with electrical resistance tomography under model uncertainties
2010 · A. Lehikoinen, J. M. J. Huttunen, et al. · Water Resources Research · 52
Approximation error analysis in nonlinear state estimation with an application to state-space identification
2007 · J M J Huttunen, J P Kaipio · Inverse Problems · 50
Estimation of groundwater storage from seismic data using deep learning
2019 · Timo Lähivaara, Alireza Malehmir, et al. · Geophysical Prospecting · 41
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Deep Learning OFDM Receivers for Improved Power Efficiency and Coverage
2023 · Jaakko Pihlajasalo, Dani Korpi, et al. · IEEE Transactions on Wireless Communications · 38
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DeepRx MIMO: Convolutional MIMO Detection with Learned Multiplicative Transformations
2021 · Dani Korpi, Mikko Honkala, et al. · International Conference on Communications · 37
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Determination of heterogeneous thermal parameters using ultrasound induced heating and MR thermal mapping
2006 · Janne M J Huttunen, Tomi Huttunen, et al. · Physics in Medicine and Biology · 34
3D thermal tomography with experimental measurement data
2014 · J.M. Toivanen, T. Tarvainen, et al. · International Journal of Heat and Mass Transfer · 30
Cauchy difference priors for edge-preserving Bayesian inversion
2019 · Markku Markkanen, Lassi Roininen, et al. · Journal of Inverse and Ill-Posed Problems · 29
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Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography
2017 · Lähivaara, Timo, Kärkkäinen, Leo, et al. · UEF eRepo (University of Eastern Finland) · 28
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DeepTx: Deep Learning Beamforming With Channel Prediction
2022 · Janne M. J. Huttunen, Dani Korpi, et al. · IEEE Transactions on Wireless Communications · 23
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Model reduction in state identification problems with an application to determination of thermal parameters
2008 · Janne M.J. Huttunen, Jari P. Kaipio · Applied Numerical Mathematics · 23
Correction of Model Reduction Errors in Simulations
2018 · A. Lipponen, J. M. J. Huttunen, et al. · SIAM Journal on Scientific Computing · 20
HybridDeepRx: Deep Learning Receiver for High-EVM Signals
2021 · Jaakko Pihlajasalo, Dani Korpi, et al. · IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC) · 18
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Deep learning for prediction of cardiac indices from photoplethysmographic waveform: A virtual database approach
2019 · Janne M.J. Huttunen, Leo Kärkkäinen, et al. · International Journal for Numerical Methods in Biomedical Engineering · 17
Artificial boundary conditions and domain truncation in electrical impedance tomography. Part I: Theory and preliminary results
2015 · Daniela Calvetti, Paul J. Hadwin, et al. · Inverse Problems and Imaging · 17
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Importance sampling approach for the nonstationary approximation error method
2010 · J M J Huttunen, A Lehikoinen, et al. · Inverse Problems · 17
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Deep Learning Based OFDM Physical-Layer Receiver for Extreme Mobility
2021 · Jaakko Pihlajasalo, Dani Korpi, et al. · 2018 52nd Asilomar Conference on Signals, Systems, and Computers · 16
Thermal tomography utilizing truncated Fourier series approximation of the heat diffusion equation
2017 · J.M. Toivanen, T. Tarvainen, et al. · International Journal of Heat and Mass Transfer · 16
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Artificial boundary conditions and domain truncation in electrical impedance tomography. Part II: Stochastic extension of the boundary map
2015 · Daniela Calvetti, Paul J. Hadwin, et al. · Inverse Problems and Imaging · 16
Works count: 57
Citation count: 1,181
H-index: 18
I10-index: 27
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