Mikko J. Sillanpää

According to our database, Mikko J. Sillanpää authored at least 31 papers between 2004 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

GHSCM: Efficient maximum a posteriori inference for biological networks with the graphical horseshoe prior.

Tuomas Hautamäki, Aapo E. Korhonen, Olli Sarala, Markku Kuismin, Mikko J. Sillanpää

Inf. Sci., 2026

Proximal regularization of deep residual neural networks applied to high-dimensional genomic data.

Yuhua Fan, Ilkka Launonen, Mikko J. Sillanpää, Patrik Waldmann

Briefings Bioinform., 2026

2025

Information-Theoretic Bounds and Task-Centric Learning Complexity for Real-World Dynamic Nonlinear Systems.

Sri Satish Krishna Chaitanya Bulusu, Mikko J. Sillanpää

CoRR, September, 2025

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

tvsfglasso: Time-varying scale-free graphical lasso for network estimation from time-series data.

Markku Kuismin, Mikko J. Sillanpää

PLoS Comput. Biol., 2025

HMFGraph: Novel Bayesian approach for recovering biological networks.

Aapo E. Korhonen, Olli Sarala, Tuomas Hautamäki, Markku Kuismin, Mikko J. Sillanpää

PLoS Comput. Biol., 2025

Grouped Device Detection and Channel Estimation in MTC Using a Full Bayesian Approach.

Reijo Leinonen, Hamza Djelouat, Markku J. Juntti, Mikko J. Sillanpää

Proceedings of the 28th International Workshop on Smart Antennas, 2025

Hybrid-Channel Estimation in Extra-Large MIMO Systems Via Regularized Sparse Bayesian Learning.

Hamza Djelouat, Markku J. Juntti, Mikko J. Sillanpää, Bhaskar D. Rao

Proceedings of the 33rd European Signal Processing Conference, 2025

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., December, 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., October, 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., January, 2024

Evaluation of Sparse Proximal Multi-Task Learning for Genome-Wide Prediction.

Yuhua Fan, Ilkka Launonen, Mikko J. Sillanpää, Patrik Waldmann

IEEE Access, 2024

2023

Sequential Model Correction for Nonlinear Inverse Problems.

Arttu Arjas, Mikko J. Sillanpää, Andreas Hauptmann

SIAM J. Imaging Sci., December, 2023

BELMM: Bayesian model selection and random walk smoothing in time-series clustering.

Olli Sarala, Tanja Pyhäjärvi, Mikko J. Sillanpää

Bioinform., October, 2023

Genetic fine-mapping from summary data using a nonlocal prior improves the detection of multiple causal variants.

Ville Karhunen, Ilkka Launonen, Marjo-Riitta Järvelin, Sylvain Sebert, Mikko J. Sillanpää

Bioinform., 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

Proceedings of the IEEE International Conference on Acoustics, 2023

Device Detection and Channel Estimation in MTC with Correlated Activity Pattern.

Hamza Djelouat, Markku J. Juntti, Mikko J. Sillanpää

Proceedings of the 57th Asilomar Conference on Signals, Systems, and Computers, ACSSC 2023, Pacific Grove, CA, USA, October 29, 2023

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

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

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

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

MCPeSe: Monte Carlo penalty selection for graphical lasso.

Markku Kuismin, Mikko J. Sillanpää

Bioinform., 2021

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

Estimation of dynamic SNP-heritability with Bayesian Gaussian process models.

Arttu Arjas, Andreas Hauptmann, Mikko J. Sillanpää

Bioinform., 2020

Scaling up an Edge Server Deployment.

Lauri Lovén, Tero Lähderanta, Leena Ruha, Teemu Leppänen, Ella Peltonen, Jukka Riekki, Mikko J. Sillanpää

Proceedings of the 2020 IEEE International Conference on Pervasive Computing and Communications Workshops, 2020

Blind Hierarchical Deconvolution.

Arttu Arjas, Lassi Roininen, Mikko J. Sillanpää, Andreas Hauptmann

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

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

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

2011

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

2007

Estimating genealogies from linked marker data: a Bayesian approach.

Dario Gasbarra, Matti Pirinen, Mikko J. Sillanpää, Elja Arjas

BMC Bioinform., 2007

2004

BAPS 2: enhanced possibilities for the analysis of genetic population structure.

Jukka Corander, Patrik Waldmann, Pekka Marttinen, Mikko J. Sillanpää

Bioinform., 2004