Aki Vehtari's Publications

If a paper is not availabe on-line and you would like a copy please send me email.

Google Scholar Citations to my publications
My ResearchGate Profile
My Researcher ID page

Book
Submitted
Working paper
Peer-reviewed scientific articles
Non-refereed scientific articles
Reports
Theses
Software
Slides
Abstracts

Book

  1. Andrew Gelman, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari and Donald B. Rubin (2013). Bayesian Data Analysis, Third Edition. Chapman and Hall/CRC. [*]Winner of the 2016 De Groot Prize from the International Society for Bayesian Analysis (awarded to the author or authors of an outstanding published book in Statistical Science) [*] Publisher's webpage for the book. Home page for the book. Errata for 3rd edition. Matlab/Octave demos. Python demos. R demos.

Submitted scientific articles

  1. Andrew Gelman, Aki Vehtari, Pasi Jylänki, Tuomas Sivula, Dustin Tran, Swupnil Sahai, Paul Blomstedt, John P. Cunningham, David Schiminovich, Christian Robert (2017). Expectation propagation as a way of life: A framework for Bayesian inference on partitioned data. arXiv preprint arXiv:1412.4869.

  2. Kristiina Santalahti, Aki Havulinna, Mikael Maksimow, Tanja Zeller, Stefan, Blankenberg, Aki Vehtari, Heikki Joensuu, Sirpa Jalkanen, Veikko Salomaa, and Marko Salmi (2017). Plasma levels of growth factors predict mortality in a general population: a prospective cohort study.

  3. Marko Järvenpää, Michael Gutmann, Aki Vehtari, Pekka Marttinen (2016). Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria. arXiv preprint arXiv:1610.06462.

  4. Eero Siivola, Juho Piironen and Aki Vehtari (2016). Automatic monotonicity detection for Gaussian Processes. arXiv preprint arXiv:1610.05440.

  5. Sebastian Weber, Andrew Gelman, Bob Carpenter, Daniel Lee, Michael Betancourt, Aki Vehtari, Amy Racine (2016). Hierarchical expectation propagation for Bayesian aggregation of average data. arXiv preprint arXiv:1602.02055.

  6. Michael Riis Andersen, Aki Vehtari, Ole Winther and Lars Kai Hansen (2015). Bayesian inference for spatio-temporal spike and slab priors. arXiv preprint arXiv:1509.04752.

  7. Aki Vehtari, Andrew Gelman and Jonah Gabry (2016). Pareto smoothed importance sampling. arXiv preprint arXiv:1507.02646. Matlab code. Python code. R code.

  8. Dmitry Smirnov, Fanny Lachat, Tomi Peltola, Juha M. Lahnakoski, Olli-Pekka Koistinen, Enrico Glerean, Aki Vehtari, Riitta Hari, Mikko Sams and Lauri Nummenmaa (2015). Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humans.

Working papers

  1. Seth Flaxman, Andrew Gelman, Daniel Neill, Alex Smola, Aki Vehtari, and Andrew Gordon Wilson (2015), Fast hierarchical Gaussian processes. Preprint.

Peer-reviewed scientific articles

  1. Juho Piironen and Aki Vehtari (2017). On the Hyperprior Choice for the Global Shrinkage Parameter in the Horseshoe Prior. Journal of Machine Learning Research: Workshop and Conference Proceedings (AISTATS 2017 Proceedings), accepted for publication. arXiv preprint arXiv:1610.05559.

  2. Juho Piironen and Aki Vehtari (2017). Comparison of Bayesian predictive methods for model selection. Statistics and Computing, 27(3):711-735. doi:10.1007/s11222-016-9649-y. First Online 07 April 2016. arXiv preprint arXiv:1503.08650.
    Supplement: Juho Piironen and Aki Vehtari (2015). Projection predictive variable selection using Stan+R. arXiv preprint arXiv:1508.02502. Code

  3. Olli-Pekka Pulkka, Bengt Nilsson, Maarit Sarlomo-Rikala, Peter Reichardt, Mikael Eriksson, Kirsten Sundby Hall, Eva Wardelmann, Aki Vehtari, Heikki Joensuu, and Harri Sihto (2017). SLUG transcription factor: A pro-survival and prognostic factor in gastrointestinal stromal tumour. British Journal of Cancer, accepted for publication.

  4. Olli-Pekka Koistinen, Emile Maras, Aki Vehtari and Hannes Jónsson (2016). Minimum energy path calculations with Gaussian process regression. In Nanosystems: Physics, Chemistry, Mathematics, 7(6):925–935. Online.

  5. Juha Salmi, Olli-Pekka Koistinen, Enrico Glerean, Pasi Jylänki, Aki Vehtari, Iiro P. Jääskeläinen, Sasu Mäkelä, Lauri Nummenmaa, Katarina Nummi-Kuisma, Ilari Nummi and Mikko Sams (2016). Distributed neural signatures of natural audiovisual speech and music in the human auditory cortex. In NeuroImage, In Press, doi:10.1016/j.neuroimage.2016.12.005. Online.

  6. Heikki Joensuu, Eva Wardelmann, Harri Sihto, Mikael Eriksson, Kirsten Sundby Hall, Annette Reichardt, Jörg T. Hartmann, Daniel Pink, Silke Cameron, Peter Hohenberger, Salah-Eddin Al-Batran, Marcus Schlemmer, Sebastian Bauer, Bengt Nilsson, Raija Kallio, Jouni Junnila, Aki Vehtari and Peter Reichardt (2016). Effect of KIT and PDGFRA Mutations on Survival in Patients With Gastrointestinal Stromal Tumor Treated With Adjuvant Imatinib: An Analysis of a Randomized Trial. In JAMA Oncology, Published online March 23, 2017. doi:10.1001/jamaoncol.2016.5751. Online.

  7. Santosh Tirunagari, Simon C Bull, Aki Vehtari, Christopher Farmer, Simon de Lusignan and Norman Poh (2016). Automatic Detection of Acute Kidney Injury Episodes from Primary Care Data. In 2016 IEEE Symposium Series on Computational Intelligence (SSCI), doi:10.1109/SSCI.2016.7849885. Online.

  8. Aki Vehtari, Andrew Gelman and Jonah Gabry (2016). Practical Bayesian model evaluation using leave-one-out cross-validation and WAIC. In Statistics and Computing, doi:10.1007/s11222-016-9696-4. Online. arXiv preprint arXiv:1507.04544. Matlab code. Python code. R code.

  9. Juho Piironen and Aki Vehtari (2016). Projection predictive input variable selection for Gaussian process models. In 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), doi:10.1109/MLSP.2016.7738829. arXiv preprint arXiv:1510.04813. Online.

  10. Aki Vehtari, Tommi Mononen, Ville Tolvanen, Tuomas Sivula and Ole Winther (2016). Bayesian leave-one-out cross-validation approximations for Gaussian latent variable models. Journal of Machine Learning Research, 17(103):1−38. Online. arXiv preprint arXiv:1412.7461.

  11. Alan Saul, James Hensman, Aki Vehtari, Neil Lawrence (2016). Chained Gaussian processes. Journal of Machine Learning Research: Workshop and Conference Proceedings (AISTATS 2016 Proceedings), 51:1431-1440. Online. arXiv preprint arXiv:1604.05263. Code

  12. Jarmo Rantonen, Jaro Karppinen, Aki Vehtari, Satu Luoto, Eira Viikari-Juntura, Markku Hupli, Antti Malmivaara and Simo Taimela (2016). Cost-effectiveness of providing patients with information on managing mild low-back symptoms. A controlled trial in an occupational health setting. BMC Public Health, 16:316, doi:10.1186/s12889-016-2974-4. Online.

  13. Dario Gasbarra, Elja Arjas, Aki Vehtari, Rémy Slama and Niels Keiding (2015). The current duration design for estimating the time to pregnancy distribution: a nonparametric Bayesian perspective. Lifetime Data Analysis, 21(4):594--625. DOI:10.1007/s10985-015-9333-0. Online. Preprint.

  14. Ville Tolvanen, Pasi Jylänki and Aki Vehtari (2014). Expectation propagation for nonstationary heteroscedastic Gaussian process regression. In Machine Learning for Signal Processing (MLSP), 2014 IEEE International Workshop on, DOI:10.1109/MLSP.2014.6958906. Online. Preprint. Code available in GPstuff toolbox.

  15. Tomi Peltola, Aki S. Havulinna, Veikko Salomaa and Aki Vehtari (2014). Hierarchical Bayesian survival analysis and projective covariate selection in cardiovascular event risk prediction. In Laskey, K. B., Jones, J. and Almond, R. (eds.) Proceedings of Eleventh UAI Bayesian Bayesian Modeling Applications Workshop (BMAW 2014), CEUR Workshop Proceedings Vol-1218, 79-88. Preprint Online. Code.

  16. Jaakko Riihimäki and Aki Vehtari (2014). Laplace approximation for logistic Gaussian process density estimation and regression. Bayesian analysis, 9(2):425-448. Online 3 February, 2014. Code available in GPstuff toolbox.

  17. Tomi Peltola, Pasi Jylänki and Aki Vehtari (2014). Expectation propagation for likelihoods depending on an inner product of two multivariate random variables. Journal of Machine Learning Research: Workshop and Conference Proceedings (AISTATS 2014 Proceedings), 33:769-777. Online. Code.

  18. Heikki Joensuu, Peter Reichardt, Mikael Eriksson, Kirsten Sundby Hall and Aki Vehtari (2014). Gastrointestinal stromal tumor: A method for optimizing the timing of CT scans in the follow-up of cancer patients. Radiology, 271(1):96-106. Online 18 November, 2013. PDF. Appendix PDF. Preprint of the statistical appendix. Related poster presented at The Third Workshop on Bayesian Inference for Latent Gaussian Models with Applications. [*]Highlighted in "This Month in Radiology".

  19. Pasi Jylänki, Aapo Nummenmaa and Aki Vehtari (2014). Expectation propagation for neural networks with sparsity-promoting priors. Journal of Machine Learning Research, 15(May):1849-1901. Online. Code.

  20. Aki Vehtari, Karita Reijonsaari, Olli-Pekka Kahilakoski, Markus V. Paananen, Willem van Mechelen, and Simo Taimela (2014). The influence of selective participation in a physical activity intervention on the generalizability of findings. Journal of Occupational and Environmental Medicine, 56(3):291–297. Online 13 January 2014

  21. Jarmo Rantonen, Aki Vehtari, Jaro Karppinen, Satu Luoto, Eira Viikari-Juntura, Markku Hupli, Antti Malmivaara and Simo Taimela (2014). Face-to-face information in addition to a booklet versus a booklet alone for treating mild back pain, a randomized controlled trial. Scandinavian journal of Work Environment & Health, 40(2):156-166. Online 2 November, 2013. PDF.

  22. Mari Myllymäki, Aila Särkkä and Aki Vehtari (2014). Hierarchical second-order analysis of replicated spatial point patterns with non-spatial covariates. Spatial Statistics, 8:104-121. Online 13 August, 2013. Preprint.

  23. Andrew Gelman, Jessica Hwang and Aki Vehtari (2014). Understanding predictive information criteria for Bayesian models. Statistics and Computing, 24(6):997-1016. Online 20 August, 2013. Preprint.

  24. Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen and Aki Vehtari (2013). GPstuff: Bayesian modeling with Gaussian processes. Journal of Machine Learning Research, 14(Apr):1175-1179. Online. Software homepage.

  25. Jaakko Riihimäki, Pasi Jylänki and Aki Vehtari (2013). Nested expectation propagation for Gaussian process classification with a multinomial probit likelihood. Journal of Machine Learning Research, 14(Jan):75-109. Online. Code available in GPstuff toolbox.

  26. Aki Vehtari and Janne Ojanen (2012). A survey of Bayesian predictive methods for model assessment, selection and comparison. Statistics Surveys, 6:142-228. Online. Errata was published in Statistics Surveys, 8 (2014), 1-1.

  27. Tomi Peltola, Pekka Marttinen and Aki Vehtari (2012). Finite adaptation and multistep moves in the Metropolis-Hastings algorithm for variable selection in genome-wide association analysis. In PLoS One, 7(11):e49445. Online.

  28. Karita Reijonsaari, Aki Vehtari, Olli-Pekka Kahilakoski, Willem van Mechelen, Timo Aro and Simo Taimela (2012). The effectiveness of physical activity monitoring and distance counseling in an occupational setting - Results from a randomized controlled trial (CoAct). BMC Public Health, 12:344 (11 May 2012). Online.

  29. Heikki Joensuu, Mikael Eriksson, Kirsten Sundby Hall, Jörg T. Hartmann, Daniel Pink, Jochen Schütte, Giuliano Ramadori, Peter Hohenberger, Justus Duyster, Salah-Eddin Al-Batran, Marcus Schlemmer, Sebastian Bauer, Eva Wardelmann, Maarit Sarlomo-Rikala, Bengt Nilsson, Harri Sihto, Odd R. Monge, Petri Bono, Raija Kallio, Aki Vehtari, Mika Leinonen, Thor Alvegård and Peter Reichardt (2012). One vs three years of adjuvant imatinib for operable gastrointestinal stromal tumor: A randomized trial. The Journal of American Medical Association, 307(12):1265-1272. Online. [*]Featured article. [*]Top 10 Journal Watch Oncology and Hematology story.

  30. 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 (2012). Risk of gastrointestinal stromal tumour recurrence after surgery: an analysis of pooled population-based cohorts. In The Lancet Oncology, 13(3):265-274. Published Online: 07 December 2011. Statistical appendix. [*]Commented in editorial. [*]Online risk calculator.

  31. 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. NeuroImage, 60(2):1517-1527. Online, Preprint.

  32. 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. PLoS ONE, 7(1):e29115. Online. Code.

  33. 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. Online. PDF. Statistical Appendix.. [*]Editor's choice.

  34. Pasi Jylänki, Jarno Vanhatalo and Aki Vehtari (2011). Robust Gaussian process regression with a Student-t likelihood. Journal of Machine Learning Research, 12(Nov):3227-3257. Online. Code available in GPstuff toolbox.

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

  36. Jaakko Riihimäki and Aki Vehtari (2010). Gaussian processes with monotonicity information. Journal of Machine Learning Research: Workshop and Conference Proceedings, 9:645-652, (AISTATS 2010 Proceedings). Online. Code available in GPstuff toolbox.

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

  38. 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. PDF.

  39. Elina Parviainen and Aki Vehtari (2010). Explaining classification by finding response-related subgroups in data. In Ma, J. et al, eds., Proceedings of the 11th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD2010, pp. 69-75, IEEE Computer Society.

  40. 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. Online.

  41. 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. Online 13 November 2009.

  42. 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. Online.

  43. 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.

  44. 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.

  45. Elina Parviainen and Aki Vehtari (2009). Features and metric from a classifier improve visualizations with dimension reduction. In Alippi et al, eds. Artificial Neural Networks - ICANN 2009, part II, pp. 225--234, Springer.

  46. 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. Online 8 May 2008.

  47. 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 (UAI 2008), pp. 571-578, AUAI Press. Online.

  48. 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.

  49. 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. Online.

  50. 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.

  51. 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. Online.

  52. 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. Online.

  53. 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. Online 16 March 2007.

  54. 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. Online 12 February 2007.

  55. 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. Online 22 February 2007, preprint PDF.

  56. 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.

  57. 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.

  58. 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.

  59. 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.

  60. 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.

  61. 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.

  62. 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.

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

  64. 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). Online. Preprint (without printer's errors).

  65. 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.

  66. 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.

  67. 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.

  68. 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.

  69. 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.

  70. 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.

  71. 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.

  72. 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.

  73. 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. PDF

  74. 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. PDF.

  75. 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. PDF.

  76. 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.

  77. 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.

  78. 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. Andrew Gelman and Aki Vehtari (2017). Consensus Monte Carlo using expectation propagation (Discussion to 'Comparing Consensus Monte Carlo Strategies for Distributed Bayesian Computation' by Steve Scott.) Brazilian Journal of Probability and Statistics, to appear. Preprint.

  2. Andrew Gelman and Aki Vehtari (2014). Discussion to 'Estimation and Accuracy after Model Selection ' by Bradley Efron. Journal of the American Statistical Association, 109(507):1015-1016. Online. Preprint.

  3. Aki Vehtari and Janne Ojanen (2012). Discussion to 'Catching up faster by switching sooner: a predictive approach to adaptive estimation with an application to the AIC-BIC dilemma' by Tim van Erven , Peter Grünwald and Steven de Rooij. Journal of the Royal Statistical Society, Series B (Statistical Methodology), 74(3):411-412. Available online 12 April 2012)

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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.

  10. 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. Andrew Gelman, Aki Vehtari, Pasi Jylänki, Christian Robert, Nicolas Chopin and John P. Cunningham (2014). Expectation propagation as a way of life. arXiv preprint arXiv:1412.4869v1.

  2. Pasi Jylänki, Aapo Nummenmaa, Aki Vehtari (2013). Expectation Propagation for Neural Networks with Sparsity-promoting Priors. arXiv:1303.6938. PDF.

  3. Jaakko Riihimäki and Aki Vehtari (2012). Laplace approximation for logistic Gaussian process density estimation. arXiv:1211.0174. PDF.

  4. Jarno Vanhatalo, Jaakko Riihimäki, Jouni Hartikainen, Pasi Jylänki, Ville Tolvanen, Aki Vehtari (2012-2013). Bayesian Modeling with Gaussian Processes using the GPstuff Toolbox. arXiv:1206.5754. PDF.

  5. 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.

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

  7. 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.

  8. 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.

  9. 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.)

  10. 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.)

  11. 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-). GPStuff - Gaussian process models for Bayesian analysis (for Matlab and Octave, over 100000 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.

Slides

Abstracts

  1. H. Sihto, O.P. Pulkka, B. Nilsson, M. Sarlomo-Rikala, P. Reichardt, M. Eriksson, K. Sundby Hall, E. Wardelmann, A. Vehtari, H. Joensuu (2016). SLUG transcription factor promotes cell proliferation and predicts outcome of patients with gastrointestinal stromal tumor. European Journal of Cancer. Online.

  2. Jeff Sperinde, Weidong Huang, Aki Vehtari, Ahmed Chenna, Pirkko-Liisa Kellokumpu-Lehtinen, John Winslow, Petri Bono, Yolanda Lie, Jodi Weidler, and Heikki Joensuu (2015). Quantitative p95HER2 and HER2 correlations with outcome in the FinHer trial [abstract]. In Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Cancer Research, 75(9 Supplement):Abstract nr P3-06-03. Online.

  3. Arno Solin, Simo Särkkä, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, Fa-Hsuan Lin (2014). Catching Physiological Noise: Comparison of DRIFTER in Image and k-Space. In Proceedings of ISMRM 2014 (abstract and poster).

  4. Arno Solin, Simo Särkkä, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, Simo Vanni, and Fa-Hsuan Lin (2013). Volumetric Space-Time Structure of Physiological Noise in BOLD fMRI. In Proceedings of ISMRM 2013 (abstract and poster).

  5. Simo Särkkä, Arno Solin, Aapo Nummenmaa, Aki Vehtari, Toni Auranen, Simo Vanni and Fa-Hsuan Lin (2012). Identification of Spatio-Temporal Oscillatory Signal Structure in Cerebral Hemodynamics Using DRIFTER. Proceedings of ISMRM 2012. (E-Poster, Abstract)

  6. Simo Särkkä, Aapo Nummenmaa, Arno Solin, Aki Vehtari, Thomas Witzel, Toni Auranen, Simo Vanni, Matti S. Hämäläinen, and Fa-Hsuan Lin. Dynamical statistical modeling of physiological noise for fast BOLD fMRI. In Proceedings of ISMRM 2011. (E-Poster)


Aki Vehtari
Last modified: 2012-11-19