Aki Vehtari's Publications

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Google Scholar Citations to my publications

Peer-reviewed scientific articles
Non-refereed scientific articles
Reports
Theses
Software

Peer-reviewed scientific articles
  1. [new] Heikki Joensuu, Aki Vehtari, Jaakko Riihimäki, Toshirou Nishida, Sonja E Steigen, Peter Brabec, Lukas Plank, Bengt Nilsson, Claudia Cirilli, Chiara Braconi, Andrea Bordoni, Magnus K Magnusson, Zdenek Linke, Jozef Sufliarsky, Federico Massimo, Jon G Jonasson, Angelo Paolo Dei Tos and Piotr Rutkowski (2011). Risk of gastrointestinal stromal tumour recurrence after surgery: an analysis of pooled population-based cohorts. In The Lancet Oncology, Early online publication. [*]Commented in editorial.

  2. [new] Simo Särkkä, Arno Solin, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, Simo Vanni and Fa-Hsuan Lin (2012). Dynamic Retrospective Filtering of Physiological Noise in BOLD fMRI: DRIFTER. In NeuroImage, Accepted for publication. Preprint.

  3. [new] Tomi Peltola, Pekka Marttinen, Antti Jula, Veikko Salomaa, Markus Perola and Aki Vehtari (2012). Bayesian variable selection in searching for additive and dominant effects in genome-wide data. In PLoS ONE, 7(1):e29115. Available online.

  4. [new]Jarmo Rantonen, Satu Luoto, Aki Vehtari, Markku Hupli, Jaro Karppinen, Antti Malmivaara and Simo Taimela (2012). The effectiveness of two active interventions compared to self-care advice in employees with non-acute low back symptoms. A randomised, controlled trial with a 4-year follow-up in the occupational health setting. Occupational and Environmental Medicine, 69(1):12-20. Available online. [*]Editor's choice.

  5. [new] Pasi Jylänki, Jarno Vanhatalo and Aki Vehtari (2011). Gaussian process regression with a Student-t likelihood. In Journal of Machine Learning Research, 12(Nov):3227-3257. Available online. Code available in GPstuff toolbox.

  6. Jarno Vanhatalo, Pia Mäkelä and Aki Vehtari (2010). Alkoholikuolleisuuden alueelliset erot Suomessa 2000-luvun alussa. Yhteiskuntapolitiikka, 75(3):265-273. (Available online in Finnish) (English translation: Regional differences in alcohol mortality in Finland in the early 2000s) (Online maps in Finnish)

  7. Jaakko Riihimäki and Aki Vehtari (2010). Gaussian processes with monotonicity information. In Journal of Machine Learning Research: Workshop and Conference Proceedings, 9:645-652, AISTATS2010 special issue. (abstract, PDF).

  8. Jarno Vanhatalo, Ville Pietiläinen and Aki Vehtari (2010). Approximate inference for disease mapping with sparse Gaussian processes. Statistics in Medicine, 29(15):1580-1607. (Available online).

  9. Jarno Vanhatalo and Aki Vehtari (2010). Speeding up the binary Gaussian process classification. In P. Grünwald and P. Spirtes, editors, Proceedings of the 26th Conference on Uncertainty in Artificial Intelligence (UAI 2010), pp. 623-632, AUAI Press. (Available online).

  10. Karita Reijonsaari, Aki Vehtari, Willem Van Mechelen, Timo Aro and Simo Taimela (2009). The effectiveness of physical activity monitoring and distance counselling in an occupational health setting - a research protocol for a randomised controlled trial (CoAct). BMC Public Health, 9:494, (Available online).

  11. Jaakko Riihimäki, Reijo Sund and Aki Vehtari (2009). Analysing the length of care episode after hip fracture: a nonparametric and a parametric Bayesian approach. Health Care Management Science, 10.1007/s10729-009-9121-z (Available online 13 November 2009).

  12. Jarno Vanhatalo, Pasi Jylänki and Aki Vehtari (2009). Gaussian process regression with Student-t likelihood. In Y. Bengio et al, editors, Advances in Neural Information Processing Systems 22, pp. 1910-1918, NIPS Foundation (Available online).

  13. Petri Korhonen, Terhi Husa, Teijo Konttila, Ilkka Tierala, Markku Mäkijärvi, Heikki Väänänen, Janne Ojanen, Aki Vehtari and Lauri Toivonen (2009). Fragmented QRS in prediction of cardiac deaths and heart failure hospitalizations after myocardial infarction. Annals of Noninvasive Electrocardiology, 15(2):130--137.

  14. Reijo Sund, Jaakko Riihimäki, Matti Mäkelä, Aki Vehtari, Peter Lüthje, Tiina Huusko and Unto Häkkinen (2009). Modeling the length of care episode after hip fracture: does the type of fracture matter? Scandinavian Journal of Surgery, 98(3):169-174. (Available online)

  15. Toni Auranen, Aapo Nummenmaa, Simo Vanni, Aki Vehtari, Matti S. Hämäläinen, Jouko Lampinen and Iiro P. Jääskeläinen (2009). Automatic fMRI-guided MEG multidipole localization for visual responses. Human Brain Mapping, 30(4):1087-1099 (Available online 8 May 2008)

  16. Jarno Vanhatalo and Aki Vehtari (2008). Modelling local and global phenomena with sparse Gaussian processes. In David McAllester and Petri Myllymäki, editors, Proceedings of the 24th Conference on Uncertainty in Artificial Intelligence, pp. 571-578, AUAI Press. (Available online)

  17. Taru Tukiainen, Tuulia Tynkkynen, Ville-Petteri Mäkinen, Pasi Jylänki, Antti Kangas, Johanna Hokkanen, Aki Vehtari, Olli Gröhn, Merja Hallikainen, Hilkka Soininen, Miia Kivipelto, Per-Henrik Groop, Kimmo Kaski, Reino Laatikainen, Pasi Soininen, Tuula Pirttilä and Mika Ala-Korpela (2008). A multi-metabolite analysis of serum by 1H NMR spectroscopy: early systemic signs of Alzheimer's disease. Biochemical and Biophysical Research Communications, 375(3):356-61.

  18. Aki Vehtari, Ville-Petteri Mäkinen, Pasi Soininen, Petri Ingman, Sanna M. Mäkelä, Markku J. Savolainen, Minna L. Hannuksela, Kimmo Kaski and Mika Ala-Korpela (2007). A novel Bayesian approach to quantify clinical variables and to determine their spectroscopic counterparts in 1H NMR metabonomic data. BMC Bioinformatics, 8(Suppl 2):S8. (Available online)

  19. Jarno Vanhatalo and Aki Vehtari (2007). Sparse log Gaussian processes via MCMC for spatial epidemiology. In Journal of Machine Learning Research: Workshop and Conference Proceedings, 1:73-89. Gaussian Processes in Practice special issue. (abstract, PDF)

  20. Marko Tapani Sysi-Aho, Aki Vehtari, Vidya Velagapudi, Jukka Westerbacka, Laxman Yetukuri, Robert Bergholm, Marja-Riitta Taskinen, Hannele Yki-Järvinen and Matej Oresic (2007). Exploring the lipoprotein composition using Bayesian regression on serum lipidomic profiles. Bioinformatics, 23(13):i519-i528, 2007. (Available online)

  21. Aapo Nummenmaa, Toni Auranen, Matti S Hämäläinen, Iiro P Jääskeläinen, Mikko Sams, Aki Vehtari and Jouko Lampinen (2007). Automatic relevance-determination based hierarchical Bayesian MEG inversion in practice. NeuroImage, 37(3):876-889. (Available online)

  22. Toni Auranen, Aapo Nummenmaa, Matti S. Hämäläinen, Iiro P. Jääskeläinen, Jouko Lampinen, Aki Vehtari and Mikko Sams (2007). Bayesian inverse analysis of neuromagnetic data using cortically constrained multiple dipoles. Human Brain Mapping, 28(10):979-994. (Available online 16 March 2007).

  23. Aapo Nummenmaa, Toni Auranen, Matti S. Hämäläinen, Iiro P. Jääskeläinen, Jouko Lampinen, Mikko Sams and Aki Vehtari (2007). Hierarchical Bayesian estimates of distributed MEG sources: theoretical aspects and comparison of variational and MCMC methods. NeuroImage, 35(2):669-685. (Available online 12 February 2007).

  24. Simo Särkkä, Aki Vehtari and Jouko Lampinen (2007). CATS benchmark time series prediction by Kalman smoother with cross-validated noise density. Neurocomputing, 70(13-15):2331-2341. (Available online 22 February 2007, preprint PDF).

  25. Simo Särkkä, Aki Vehtari and Jouko Lampinen (2007). Rao-Blackwellized Particle Filter for Multiple Target Tracking. Information Fusion, 8(1):2-15. (online, preprint PDF)

  26. Simo Särkkä, Aki Vehtari and Jouko Lampinen (2007). Prediction of ESTSP Competition Time Series by Unscented Kalman Filter and RTS Smoother. In Amaury Lendasse, editor, Proceedings of European Symposium on Time Series Prediction (ESTSP'07), pp.1-10. (PDF)

  27. Toni Auranen, Aapo Nummenmaa, Matti S. Hämäläinen, Iiro P. Jääskeläinen, Jouko Lampinen, Aki Vehtari and Mikko Sams (2005). Bayesian analysis of the neuromagnetic inverse problem with L^p-norm priors. NeuroImage, 26(3):870-884. (revised personal version PDF)

  28. Ilkka Kalliomäki, Aki Vehtari and Jouko Lampinen (2005). Shape analysis of concrete aggregates for statistical quality modeling. Machine Vision and Applications, 16(3):197-201. (PDF)

  29. Simo Särkkä, Aki Vehtari and Jouko Lampinen (2004). Time series prediction by Kalman smoother with cross-validated noise density. In IJCNN'2004: Proceedings of the 2004 International Joint Conference on Neural Networks, Budabest, July 2004. [*] The Winner of Time Series Prediction Competition - The CATS Benchmark (PDF)

  30. Simo Särkkä, Aki Vehtari and Jouko Lampinen (2004). Rao-Blackwellized Monte Carlo data association for multiple target tracking. In Per Svensson and Johan Schubert, editors, Proceedings of the Seventh International Conference on Information Fusion, volume I, pp. 583-590. (PDF).

  31. Aki Vehtari and Jouko Lampinen (2003). Expected utility estimation via cross-validation. In J. M. Bernardo, et al., editors, Bayesian Statistics 7, pp. 701-710. Oxford University Press. (PDF)

  32. Aki Vehtari and Jouko Lampinen (2002). Bayesian model assessment and comparison using cross-validation predictive densities. Neural Computation, 14(10):2439-2468. (PDF)

  33. Jouko Lampinen and Aki Vehtari (2001). Bayesian approach for neural networks - review and case studies. Neural Networks, 14(3):7-24. (Invited article. Note that unfortunately the paper version has some printer's errors). (PDF)

  34. Jouko Lampinen and Aki Vehtari (2001). Bayesian techniques for neural networks - review and case studies. In K. Wang, J Grundespenkis and A. Yerofeyev, editors, Applied Computational Intelligence to Engineering and Business, pp. 7-15.

  35. Aki Vehtari and Jouko Lampinen (2000). Bayesian MLP neural networks for image analysis. Pattern Recognition Letters, 21(13-14):1183-1191. (Special Issue - Selected Papers from The 11th Scandinavian Conference on Image Analysis.) (PDF)

  36. Jouko Lampinen and Aki Vehtari (2000) Bayesian techniques for neural networks - review and case studies. In M. Gabbouj and P. Kuosmanen, editors, Eusipco'2000: Proceedings of the X European Signal Processing Conference, volume 2, pp. 713-720. (PDF)

  37. Aki Vehtari, Simo Särkkä and Jouko Lampinen (2000). On MCMC sampling in Bayesian MLP neural networks. In Shun-Ichi Amari, C. Lee Giles, Marco Gori and Vincenzo Piuri, editors, IJCNN'2000: Proceedings of the 2000 International Joint Conference on Neural Networks, volume I, pp. 317-322. IEEE. (PDF)

  38. Aki Vehtari and Jouko Lampinen (2000). Bayesian MLP neural networks - review and case studies. In Leena Yliniemi and Esko Juuso, editors, TOOLMET2000: Proceedings of the Tool Environments and Development Methods for Intelligent Systems, pp. 120-133. Oulun Yliopistopaino.

  39. Aki Vehtari and Jouko Lampinen (2000). Bayesian neural networks: Case studies in industrial applications. In Y. Suzuki, R. Roy, S. J. Ovaska, T. Furuhashi and Y. Dote, editors, Soft Computing in Industrial Applications, pp. 411-420. Springer-Verlag.

  40. Aki Vehtari and Jouko Lampinen (1999). Bayesian neural networks with correlating residuals. In IJCNN'99: Proceedings of the 1999 International Joint Conference on Neural Networks [CD-ROM], paper number 2061. IEEE. (PDF)

  41. Jouko Lampinen, Aki Vehtari and Kimmo Leinonen (1999). Application of Bayesian neural network in electrical impedance tomography. In IJCNN'99: Proceedings of the 1999 International Joint Conference on Neural Networks [CD-ROM], paper number 375. (PDF)

  42. Aki Vehtari and Jouko Lampinen (1999). Bayesian neural networks for industrial applications. In SMCIA/99: Proceedings of the 1999 IEEE Midnight-Sun Workshop on Soft Computing Methods in Industrial Applications, pp. 63-68.

  43. Aki Vehtari and Jouko Lampinen (1999). Bayesian neural networks for image analysis. In B. K. Ersboll and P. Johansen, editors, SCIA'99: Proceedings of The 11th Scandinavian Conference on Image Analysis, volume 1, pages 95-102. The Pattern Recognition Society of Denmark. (PostScript)

  44. Jouko Lampinen, Aki Vehtari and Kimmo Leinonen (1999). Using Bayesian neural network to solve the inverse problem in electrical impedance tomography. In B. K. Ersboll and P. Johansen, editors, SCIA'99: Proceedings of the 11th Scandinavian Conference on Image Analysis, volume 1, pages 87-93. The Pattern Recognition Society of Denmark. (PostScript)

  45. Jukka Heikkonen, Jari Varjo and Aki Vehtari (1999). Forest change detection via Landsat TM difference features. In SCIA'99: Proceedings of the 11th Scandinavian Conference on Image Analysis, volume 1, pages 157-164. The Pattern Recognition Society of Denmark.

  46. Aki Vehtari, Jukka Heikkonen, Jouko Lampinen and Jouni Juujärvi (1998). Using Bayesian neural networks to classify forest scenes. In David P. Casasent, editor, Intelligent Robots and Computer Vision XVII: Algorithms, Techniques and Active Vision, volume 3522 of Proceedings of SPIE, pp. 66-73. SPIE.

  47. Aki Vehtari, Jouni Juujärvi, Jukka Heikkonen and Jouko Lampinen (1998). Forest scene classification: Comparison of classifiers. In Proceedings of STeP'98, pp. 152-160.

Non-refereed scientific articles
  1. Aki Vehtari and Jarno Vanhatalo (2011). Discussion to 'Riemann manifold Langevin and Hamiltonian Monte Carlo methods' by Mark Girolami and Ben Calderhead. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 73(2):201 (Available online 3 March 2011)

  2. Jarno Vanhatalo and Aki Vehtari (2009). Discussion to 'Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations' by Håvard Rue, Sara Martino and Nicolas Chopin. Journal of the Royal Statistical Society, Series B (Statistical Methodology)., 71(2):383 (Available online 6 April 2009)

  3. Aki Vehtari (2007). Discussion to `Some Aspects of Bayesian Model Selection for Prediction' by Chakrabarti, A. and Ghosh, J. K.. In J. M. Bernardo, et al., editors, Bayesian Statistics 8, p. 83-84. Oxford University Press.

  4. Aki Vehtari (2003). Discussion to `Hierarchical multivariate CAR models for spatio-temporally correlated survival data' by Carlin B. P. and Banerjee, S. In J. M. Bernardo, et al., editors, Bayesian Statistics 7, p. 61. Oxford University Press. (PDF)

  5. Aki Vehtari (2003). Discussion to `Bayesian Treed Generalized Linear Models' by Chipman, H. A., George, E. I. and McCulloch R. E. In J. M. Bernardo, et al., editors, Bayesian Statistics 7, p. 101. Oxford University Press. (PDF)

  6. Aki Vehtari (2002). Discussion to `Bayesian measures of model complexity and fit' by Spiegelhalter, D. J., Best, N. G., Carlin, B. P. and van der Linde, A. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 64(4):620. (PDF)

  7. Jouko Lampinen and Aki Vehtari (2002). Bayesilaiset menetelmät hahmontunnistuksessa (in Finnish). In J. Iivarinen, S. Kaski and E. Oja, editors, Neljännesvuosisata Hatutusta: Hahmontunnistustutkimus Suomessa 1977-2002, pp. 86-96. Suomen hahmontunnistustutkimuksen seura ry. (HTML)

Reports
  1. Jarno Vanhatalo, Pia Mäkelä, ja Aki Vehtari (2010). Regional differences in alcohol mortality in Finland in the early 2000s. Report A20, Department of Biomedical Engineering and Computational Science Publications, Helsinki University of Technology. (PDF)

  2. Aki Vehtari and Jouko Lampinen (2004). Model Selection via Predictive Explanatory Power. Report B38, Laboratory of Computational Engineering, Helsinki University of Technology. (PDF)

  3. Simo Särkkä, Toni Tamminen, Aki Vehtari and Jouko Lampinen (2004). Probabilistic methods in multiple target tracking - Review and bibliography. Report B36, Laboratory of Computational Engineering, Helsinki University of Technology. (PDF)

  4. Aki Vehtari and Jouko Lampinen (2002). Bayesian input variable selection using posterior probabilities and expected utilities. Report B31, Laboratory of Computational Engineering, Helsinki University of Technology. (Revised version of Report B28). (PDF)

  5. Aki Vehtari and Jouko Lampinen (2001). Bayesian input variable selection using cross-validation predictive densities and reversible jump MCMC. Report B28, Laboratory of Computational Engineering, Helsinki University of Technology. (Superseded by Aki Vehtari and Jouko Lampinen (2002). Bayesian Input Variable Selection Using Posterior Probabilities and Expected Utilities. Report B31, Laboratory of Computational Engineering, Helsinki University of Technology.)

  6. Aki Vehtari and Jouko Lampinen (2001). Bayesian model assesment and comparison using cross-validation predictive densities. Report B27, Laboratory of Computational Engineering, Helsinki University of Technology. (Revised version of Report B23). (Superseded by Aki Vehtari and Jouko Lampinen (2002). Bayesian model assessment and comparison using cross-validation predictive densities. Neural Computation, 14(10):2439-2468.)

  7. Aki Vehtari and Jouko Lampinen (2001). On Bayesian model assesment and choice using cross-validation predictive densities. Report B23, Laboratory of Computational Engineering, Helsinki University of Technology. (Superseded by Aki Vehtari and Jouko Lampinen (2002). Bayesian model assessment and comparison using cross-validation predictive densities. Neural Computation, 14(10):2439-2468.) (Appendix in PDF)

Theses
  1. Aki Vehtari (2001). Bayesian model assessment and selection using expected utilities. Dissertation for the degree of Doctor of Science in Technology, Helsinki University of Technology. (Abstract) (PDF) (Väitöstiedote).
    [*] Dissertation was awarded: The best doctoral dissertation award in the field of pattern recognition in 2000-2001 in Finland issued by the Pattern Recognition Society of Finland.

  2. Aki Vehtari (1997). Pumppausprosessin neuroverkkomallinnus (Neural network modelling of pumping process). Master's thesis, Helsinki University of Technology.

Software
  1. Jarno Vanhatalo, Aki Vehtari et al (2008-2011). GPStuff - Gaussian process models for Bayesian analysis (for Matlab, over 90000 lines of code). (web page).

  2. Aki Vehtari et al (2004-2009). MCMCStuff - MCMC Methods for MLP and GP and Stuff (for Matlab, over 13000 lines of code) (web page).

  3. Simo Särkkä and Aki Vehtari (2003-2005). MCMCDiag -- MCMC diagnostics (for Matlab) (web page).

  4. Simo Särkkä and Aki Vehtari (2003). FBM tools (for Matlab) (web page).

Aki Vehtari
Last modified: 2012-02-03