Researchers
PhD students
Research assistants
Visiting researchers
Former PhD students
Former Postdocs
Former group members (Master's students, visitors, etc)
Machine learning methodology
Applications
Raj, V., Cui, T., Heinonen, M. and Marttinen, P. (2023). Incorporating functional summary information in Bayesian neural networks using a Dirichlet process likelihood approach. The 26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), accepted.
Cui, T., Kumar, Y., Marttinen, P., and Kaski, S. (2022). Deconfounded Representation Similarity for Comparison of Neural Networks. Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), accepted. Preprint
Rissanen, S. and Marttinen, P. (2021). A Critical Look at the Consistency of Causal Estimation with Deep Latent Variable Models. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), pp. 4207-4217. Available online
Cui, T., Havulinna, A., Marttinen, P.*, and Kaski, S.* (2021). Informative Bayesian Neural Network Priors for Weak Signals. Bayesian Analysis, 1-31. (*equal contribution) Advance publication
Järvenpää, M., Gutmann, M.U., Vehtari, A., and Marttinen, P. (2021). Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations. Bayesian Analysis, 16(1):147-178. Available online
Järvenpää, M., Gutmann, M.U., Pleska, A., Vehtari, A., and Marttinen, P. (2019). Efficient acquisition rules for model-based approximate Bayesian computation. Bayesian Analysis, 14(2):595-622. Available online
Gillberg, J., Marttinen, P., Pirinen, M., Kangas, A.-J., Soininen, P., Ali, M., Havulinna, A. S., Järvelin, M.-R., Ala-Korpela, M., and Kaski, S. (2016). Multiple output regression with latent noise. Journal of Machine Learning Research, 17:1-35. Available online
Ji, S. and Marttinen, P. (2023). Patient Outcome and Zero-shot Diagnosis Prediction with Hypernetwork-guided Multitask Learning. The 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), accepted. Preprint
Marttinen, P. and Hanage, W.P. (2017). Speciation trajectories in recombining bacterial species. PLOS Computational Biology, 13(7):e1005640. Available online
Mostowy, R., Croucher, N.J., Andam, C.P., Corander, J., Hanage, W.P., and Marttinen, P. (2017). Efficient inference of recent and ancestral recombination within bacterial populations. Molecular Biology and Evolution, 34(5):1167-1182. Available online
Marttinen, P., Croucher, N.J., Gutmann, M.U., Corander, J. and Hanage, W.P. (2015). Recombination produces coherent bacterial species clusters in both core and accessory genomes. Microbial Genomics, 1, doi:10.1099/mgen.0.000038, Available online (Supplement)
Marttinen, P., Pirinen, M., Sarin, A.P., Gillberg, J., Kettunen, J., Surakka, I., Kangas, A.J., Soininen, P., O’Reilly, P.F., Kaakinen, M., Kähönen, M., Lehtimäki, T., Ala-Korpela, M., Raitakari, O.T., Salomaa, V., Järvelin, M.-R., Ripatti, S. and Kaski, S. (2014). Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression. Bioinformatics, 30(14):2026-34. Available online
Marttinen, P., Hanage, W.P., Nicholas, J.C., Connor, T.C., Harris, S.R., Bentley, S.D. and Corander, J. (2012). Detection of recombination events in bacterial genomes from large population samples. Nucleic Acids Research, 40(1): e6. Available online
Corander, J. and Marttinen, P. (2006). Bayesian identification of admixture events using multi-locus molecular markers. Molecular Ecology, 15:2833-2843. Link
Chewapreecha, C., Marttinen, P., Croucher, N.J.,Salter, S.J., Harris, S.R., Mather, A.E.,Hanage, W.P., Goldblatt, D., Nosten, F.H., Turner, C., Turner, P., Bentley, S.D. and Parkhill, J. (2014). Comprehensive identification of single nucleotide polymorphisms associated with beta-lactam resistance within pneumococcal mosaic genes. PLoS Genetics, 10(8):e1004547. Available online
Kashtan, N., Roggensack, S.E., Rodrigue, S., Thompson, J.W., Biller, S.J., Coe, A., Ding, H., Marttinen, P., Malmstrom, R.R., Stocker, R., Follows, M.J., Stepanauskas, R. and Chisholm, S.W. (2014). Single-cell genomics reveals hundreds of coexisting subpopulations in wild Prochlorococcus. Science, 344(6182): 416-420. Link
Chewapreecha, C., Harris, S.R., Croucher, N.J., Turner, C., Marttinen, P., Cheng, L., Pessia, A., Aanensen, D.M., Mather, A.E., Page, A.J., Salter, S.J., Harris, D., Nosten, F., Goldblatt, D., Corander, J., Parkhill, J., Turner, P. and Bentley, S.D. (2014). Dense genomic sampling identifies highways of pneumococcal recombination. Nature Genetics, 46: 305-309. Link
I have authored/co-authored the following software:
Machine Learning: 2022
Special course: Elements of Causal Inference: 2022, 2021
Machine Learning: Advanced Probabilistic Methods: 2022, 2021, 2020, 2018, 2017, 2016, 2015
Computational Genomics: 2020, 2019, 2018, 2017 fall, 2017 spring
Data Science: 2019
Information visualization: 2015
Introduction to Bayesian Modeling: 2011, 2010
Special Course in Bayesian Modeling (Bayesian Networks): 2010