BAPS 2: enhanced possibilities for the analysis of genetic population structure. - Jukka Corander; Patrik Waldmann; Pekka Marttinen; Mikko J. Sillanpää (Bioinform., 2004)

Estimating genealogies from linked marker data: a Bayesian approach. - Dario Gasbarra; Matti Pirinen; Mikko J. Sillanpää; Elja Arjas (BMC Bioinform., 2007)

Estimating Haplotype Frequencies by Combining Data from Large DNA Pools with Database Information. - Dario Gasbarra; Sangita Kulathinal; Matti Pirinen; Mikko J. Sillanpää (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

A Gaussian process model and Bayesian variable selection for mapping function-valued quantitative traits with incomplete phenotypic data. - Jarno Vanhatalo; Zitong Li; Mikko J. Sillanpää (Bioinform., 2019)

Edge server placement with capacitated location allocation. - Tero Lähderanta; Teemu Leppänen; Leena Ruha; Lauri Lovén; Erkki Harjula; Mika Ylianttila; Jukka Riekki; Mikko J. Sillanpää (CoRR, 2019)

Blind Hierarchical Deconvolution. - Arttu Arjas; Lassi Roininen; Mikko J. Sillanpää; Andreas Hauptmann (MLSP, 2020)

Scaling up an Edge Server Deployment. - Lauri Lovén; Tero Lähderanta; Leena Ruha; Teemu Leppänen; Ella Peltonen; Jukka Riekki; Mikko J. Sillanpää (PerCom Workshops, 2020)

Estimation of dynamic SNP-heritability with Bayesian Gaussian process models. - Arttu Arjas; Andreas Hauptmann; Mikko J. Sillanpää (Bioinform., 2020)

Personalized mental stress detection with self-organizing map: From laboratory to the field. - Jaakko Tervonen; Sampsa Puttonen; Mikko J. Sillanpää; Leila Hopsu; Zsolt Homorodi; Janne Keränen; Janne Pajukanta; Antti Tolonen; Arttu Lämsä; Jani Mäntyjärvi (Comput. Biol. Medicine, 2020)

MCPeSe: Monte Carlo penalty selection for graphical lasso. - Markku Kuismin; Mikko J. Sillanpää (Bioinform., 2021)

Neural Network Kalman filtering for 3D object tracking from linear array ultrasound data. - Arttu Arjas; Erwin J. Alles; Efthymios Maneas; Simon R. Arridge; Adrien E. Desjardins; Mikko J. Sillanpää; Andreas Hauptmann (CoRR, 2021)

Edge computing server placement with capacitated location allocation. - Tero Lähderanta; Teemu Leppänen; Leena Ruha; Lauri Lovén; Erkki Harjula; Mika Ylianttila; Jukka Riekki; Mikko J. Sillanpää (J. Parallel Distributed Comput., 2021)

Model guided trait-specific co-expression network estimation as a new perspective for identifying molecular interactions and pathways. - Juho A. J. Kontio; Tanja Pyhäjärvi; Mikko J. Sillanpää (PLoS Comput. Biol., 2021)

EDISON: An Edge-Native Method and Architecture for Distributed Interpolation. - Lauri Lovén; Tero Lähderanta; Leena Ruha; Ella Peltonen; Ilkka Launonen; Mikko J. Sillanpää; Jukka Riekki; Susanna Pirttikangas (Sensors, 2021)

Device Detection and Channel Estimation in MTC with Correlated Activity Pattern. - Hamza Djelouat; Markku J. Juntti; Mikko J. Sillanpää (ACSSC, 2023)

Machine Learning-Aided Piece-Wise Modeling Technique of Power Amplifier for Digital Predistortion. - S. S. Krishna Chaitanya Bulusu; Nuutti Tervo; Praneeth Susarla; Mikko J. Sillanpää; Olli Silvén; Markku J. Juntti; Aarno Pärssinen (ICASSP, 2023)

BELMM: Bayesian model selection and random walk smoothing in time-series clustering. - Olli Sarala; Tanja Pyhäjärvi; Mikko J. Sillanpää (Bioinform., 2023)

Sequential Model Correction for Nonlinear Inverse Problems. - Arttu Arjas; Mikko J. Sillanpää; Andreas Hauptmann (SIAM J. Imaging Sci., 2023)

Evaluation of Sparse Proximal Multi-Task Learning for Genome-Wide Prediction. - Yuhua Fan; Ilkka Launonen; Mikko J. Sillanpää; Patrik Waldmann (IEEE Access, 2024)

Capacitated spatial clustering with multiple constraints and attributes. - Tero Lähderanta; Lauri Lovén; Leena Ruha; Teemu Leppänen; Ilkka Launonen; Jukka Riekki; Mikko J. Sillanpää (Eng. Appl. Artif. Intell., 2024)

Hierarchical MTC User Activity Detection and Channel Estimation With Unknown Spatial Covariance. - Hamza Djelouat; Mikko J. Sillanpää; Markus Leinonen; Markku J. Juntti (IEEE Trans. Wirel. Commun., 2024)

Machine learning-based methods for piecewise digital predistortion in mmW 5G NR systems. - S. S. Krishna Chaitanya Bulusu; Nuutti Tervo; Praneeth Susarla; Olli Silvén; Mikko J. Sillanpää; Marko E. Leinonen; Markku J. Juntti; Aarno Pärssinen (EURASIP J. Adv. Signal Process., 2024)

Adaptive and Self-Tuning SBL With Total Variation Priors for Block-Sparse Signal Recovery. - Hamza Djelouat; Reijo Leinonen; Mikko J. Sillanpää; Bhaskar D. Rao; Markku J. Juntti (IEEE Signal Process. Lett., 2025)