Methods for Long-Term GNSS Clock Offset Prediction. - Jaakko Pihlajasalo; Helena Leppäkoski; Saara Kuismanen; Simo Ali-Löytty; Robert Piché (ICL-GNSS, 2019)

Absolute Positioning with Unsupervised Multipoint Channel Charting for 5G Networks. - Jaakko Pihlajasalo; Mike Koivisto; Jukka Talvitie; Simo Ali-Löytty; Mikko Valkama (VTC Fall, 2020)

Deep Learning Based OFDM Physical-Layer Receiver for Extreme Mobility. - Jaakko Pihlajasalo; Dani Korpi; Mikko Honkala; Janne M. J. Huttunen; Taneli Riihonen; Jukka Talvitie; Mikko A. Uusitalo; Mikko Valkama (ACSCC, 2021)

Transfer Learning for Convolutional Indoor Positioning Systems. - Roman Klus; Lucie Klus; Jukka Talvitie; Jaakko Pihlajasalo; Joaquín Torres-Sospedra; Mikko Valkama (IPIN, 2021)

HybridDeepRx: Deep Learning Receiver for High-EVM Signals. - Jaakko Pihlajasalo; Dani Korpi; Mikko Honkala; Janne M. J. Huttunen; Taneli Riihonen; Jukka Talvitie; Alberto Brihuega; Mikko A. Uusitalo; Mikko Valkama (PIMRC, 2021)

Detection of Impaired OFDM Waveforms Using Deep Learning Receiver. - Jaakko Pihlajasalo; Dani Korpi; Taneli Riihonen; Jukka Talvitie; Mikko A. Uusitalo; Mikko Valkama (SPAWC, 2022)

Deep Learning OFDM Receivers for Improved Power Efficiency and Coverage. - Jaakko Pihlajasalo; Dani Korpi; Mikko Honkala; Janne M. J. Huttunen; Taneli Riihonen; Jukka Talvitie; Alberto Brihuega; Mikko A. Uusitalo; Mikko Valkama (IEEE Trans. Wirel. Commun., 2023)

Machine Learning Physical-Layer Receivers for DFT-s-OFDM. - Jaakko Pihlajasalo; Dani Korpi; Taneli Riihonen; Jukka Talvitie; Mikko Valkama (IEEE Trans. Veh. Technol., 2025)