Publications

This page lists the publications of the Probabilistic Machine Learning group formed in 2015. The group is a fusion of two former research groups from Aalto University, the Statistical Machine Learning and Bioinformatics group and the Bayesian Methodology group. For the earlier publications of these groups, please see below.

Publication year Title First author
2019
Eeva Leena Kataja, Linnea Karlsson, Christine E. Parsons, Juho Pelto, Henri Pesonen, Tuomo Häikiö, Jukka Hyönä, Saara Nolvi, Riikka Korja, Hasse Karlsson (2019). Maternal pre- and postnatal anxiety symptoms and infant attention disengagement from emotional faces. JOURNAL OF AFFECTIVE DISORDERS, 243:280-289. [Link]
Maternal pre- and postnatal anxiety symptoms and infant attention disengagement from emotional facesKatajaPublished
Submitted
Kenneth Blomqvist, Samuel Kaski, Markus Heinonen (2018). Deep convolutional Gaussian process. [Preprint] [Code]
Deep convolutional Gaussian processBlomqvistSubmitted
2018
Pedram Daee, Tomi Peltola, Aki Vehtari, Samuel Kaski (2018). User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. INTERNATIONAL CONFERENCE ON INTELLIGENT USER INTERFACES, IUI 2018 - Proceedings of the 23rd International Conference on Intelligent User Interfaces, p. 305-310. [Preprint] [Code and data] [Link]
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for PredictionDaeePublished
2018
Jieyao Deng, Qingjun Yuan, Hiroshi Mamitsuka, Shanfeng Zhu (2018). DrugE-rank Predicting drug-target interactions by learning to rank. Methods in Molecular Biology, Methods in Molecular Biology, 1807:195-202. [Link]
DrugE-rank Predicting drug-target interactions by learning to rankDengPublished
2018
Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander (2018). Likelihood-free inference via classification. STATISTICS AND COMPUTING, 28(2):411–425. [Pre-print (First version in 2014)] [Link]
Likelihood-free inference via classificationGutmannPublished
Submitted
Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki, Samuel Kaski (2018). Deep learning with differential Gaussian process flows. [Preprint]
Deep learning with differential Gaussian process flowsHegdeSubmitted
To appear
Pashupati Hegde, Markus Heinonen, Samuel Kaski (2018). Variational zero-inflated Gaussian processes with sparse kernels. Uncertainty in Artificial Intelligence [Preprint]
Variational zero-inflated Gaussian processes with sparse kernelsHegdeAccepted/In press
2018
Antti Honkela, Mrinal Das, Arttu Nieminen, Onur Dikmen, Samuel Kaski (2018). Efficient differentially private learning improves drug sensitivity prediction. BIOLOGY DIRECT, 13(1):1-12. [Preprint] [Link]
Efficient differentially private learning improves drug sensitivity predictionHonkelaPublished
To appear
Giulio Jacucci, Oswald Barral, Pedram Daee, Markus Wenzel, Baris Serim, Tuukka Ruotsalo, Patrik Pluchino, Jonathan Freeman, Luciano Gamberini, Samuel Kaski, Benjamin Blankertz (2018). Integrating Neurophysiological Relevance Feedback in Intent Modeling for Information Retrieval. JOURNAL OF THE ASSOCIATION FOR INFORMATION SCIENCE AND TECHNOLOGY. [Link]
Integrating Neurophysiological Relevance Feedback in Intent Modeling for Information RetrievalJacucciAccepted/In press
To appear
Marko Järvenpää, Michael Gutmann, Aki Vehtari, Pekka Marttinen (2018). Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria. ANNALS OF APPLIED STATISTICS. [Preprint]
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteriaJärvenpääAccepted/In press
To appear
Marko Järvenpää, Michael Gutmann, Arijus Pleska, Aki Vehtari, Pekka Marttinen (2018). Efficient acquisition rules for model-based approximate Bayesian computation. BAYESIAN ANALYSIS. [Preprint]
Efficient acquisition rules for model-based approximate Bayesian computationJärvenpääAccepted/In press
To appear
Antti Kangasrääsiö, Samuel Kaski (2018). Inverse reinforcement learning from summary data. European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, MACHINE LEARNING. [preprint] [Link]
Inverse reinforcement learning from summary dataKangasrääsiöE-pub ahead of print
2018
Masayuki Karasuyama, Hiroshi Mamitsuka (2018). Factor Analysis on a Graph. International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, Proceedings of the Twenty-First International Conference on Artificial Intelligence and Statistics, 84:1117-1126. [Link]
Factor Analysis on a GraphKarasuyamaPublished
2018
Niina Lietzén, Lu Cheng, Robert Moulder, Heli Siljander, Essi Laajala, Taina Härkönen, Aleksandr Peet, Aki Vehtari, Vallo Tillmann, Mikael Knip, Harri Lähdesmäki, Riitta Lahesmaa (2018). Characterization and non-parametric modeling of the developing serum proteome during infancy and early childhood. SCIENTIFIC REPORTS, 8(1):1-13. [Link]
Characterization and non-parametric modeling of the developing serum proteome during infancy and early childhoodLietzénPublished
2018
Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski (2018). ELFI Engine for likelihood-free inference. JOURNAL OF MACHINE LEARNING RESEARCH, 19:1-7. [Link]
ELFI Engine for likelihood-free inferenceLintusaariPublished
2018
Hiroshi Mamitsuka (2018). Preface. Methods in Molecular Biology, Data Mining for Systems Biology Methods and Protocols, 1807:v-vi.
PrefaceMamitsukaPublished
2018
Hiroshi Mamitsuka (2018). Data Mining for Systems Biology Methods and Protocols. Methods in Molecular Biology, 1807. [Link]
Data Mining for Systems Biology Methods and ProtocolsMamitsukaPublished
2018
Hiroshi Mamitsuka (2018). Textbook of Machine Learning and Data Mining with Bioinformatics Applications.
Textbook of Machine Learning and Data Mining with Bioinformatics ApplicationsMamitsukaPublished
2018
Elsa Marques, Tomi Peltola, Samuel Kaski, Juha Klefström (2018). Phenotype-driven identification of epithelial signalling clusters. SCIENTIFIC REPORTS, 8(1):1-13. [Link]
Phenotype-driven identification of epithelial signalling clusters MarquesPublished
2018
Xiangming Meng, Sheng Wu, Michael Riis Andersen, Jiang Zhu, Zuyao Ni (2018). Efficient Recovery of Structured Sparse Signals via Approximate Message Passing with Structured Spike and Slab Prior. CHINA COMMUNICATIONS, 15(6):1-17. [Link]
Efficient Recovery of Structured Sparse Signals via Approximate Message Passing with Structured Spike and Slab PriorMengPublished
2018
Osval A. Montesinos-López, Abelardo Montesinos-López, José Crossa, José C. Montesinos-López, David Mota-Sanchez, Fermín Estrada-González, Jussi Gillberg, Ravi Singh, Suchismita Mondal, Philomin Juliana (2018). Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender Systems. G3: GENES, GENOMES, GENETICS, 8(1):131-147. [Link]
Prediction of Multiple-Trait and Multiple-Environment Genomic Data Using Recommender SystemsMontesinos-LópezPublished
2018
Dai Hai Nguyen, Canh Hao Nguyen, Hiroshi Mamitsuka (2018). SIMPLE Sparse Interaction Model over Peaks of moLEcules for fast, interpretable metabolite identification from tandem mass spectra. Annual Conference on Intelligent Systems for Molecular Biology, BIOINFORMATICS, 34(13):i323-i332. [Link]
SIMPLE Sparse Interaction Model over Peaks of moLEcules for fast, interpretable metabolite identification from tandem mass spectraNguyenPublished
2018
Teppo Niinimäki, Mikko Heikkilä, Samuel Kaski, Antti Honkela (2018). Deep Transfer Learning of Representations for Differentially Private Learning. Federated Artificial Intelligence Meeting Workshop, [Workshop home page]
Deep Transfer Learning of Representations for Differentially Private LearningNiinimäkiPublished
Submitted
Topi Paananen, Juho Piironen, Michael Andersen, Aki Vehtari (2018). Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution. [Preprint] [Code]
Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distributionPaananenSubmitted
2018
Tomi Peltola, Jussi Jokinen, Samuel Kaski (2018). Probabilistic Formulation of the Take The Best Heuristic. Annual Meeting of the Cognitive Science Society, CogSci 2018 Proceedings, p. 2214-2219. [Code] [Link]
Probabilistic Formulation of the Take The Best HeuristicPeltolaPublished
2018
Tomi Peltola (2018). Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler Projections. Workshop on Explainable Artificial Intelligence, [link]
Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler ProjectionsPeltolaPublished
Submitted
Tomi Peltola, Mustafa Celikok, Pedram Daee, Samuel Kaski (2018). Modelling User's Theory of AI's Mind in Interactive Intelligent Systems. [Preprint]
Modelling User's Theory of AI's Mind in Interactive Intelligent SystemsPeltolaSubmitted
2018
Shengwen Peng, Hiroshi Mamitsuka, Shanfeng Zhu (2018). MeSHLabeler and DeepMeSH Recent progress in large-scale MeSH indexing. Methods in Molecular Biology, Methods in Molecular Biology, 1807:203-209. [Link]
MeSHLabeler and DeepMeSH Recent progress in large-scale MeSH indexingPengPublished
2018
Irene Petersen, Tomi Peltola, Samuel Kaski, Kate R Walters, Sarah Hardoon (2018). Depression, depressive symptoms and treatments in women who have recently given birth UK cohort study. BMJ OPEN, 8(10):1-8. [link] [Link]
Depression, depressive symptoms and treatments in women who have recently given birth UK cohort studyPetersenPublished
2018
Juho Piironen, Aki Vehtari (2018). Iterative Supervised Principal Components. International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, International Conference on Artificial Intelligence and Statistics, 9-11 April 2018, Playa Blanca, Lanzarote, Canary Islands, 84. [Link] [Preprint]
Iterative Supervised Principal ComponentsPiironenPublished
Submitted
Juho Piironen, Markus Paasiniemi, Aki Vehtari (2018). Projective Inference in High-dimensional Problems: Prediction and Feature Selection. [Preprint]
Projective Inference in High-dimensional Problems: Prediction and Feature SelectionPiironenSubmitted
2018
J. Rantonen, J. Karppinen, A. Vehtari, S. Luoto, E. Viikari-Juntura, M. Hupli, A. Malmivaara, S. Taimela (2018). Effectiveness of three interventions for secondary prevention of low back pain in the occupational health setting - A randomised controlled trial with a natural course control. BMC PUBLIC HEALTH, 18(1). [Link]
Effectiveness of three interventions for secondary prevention of low back pain in the occupational health setting - A randomised controlled trial with a natural course controlRantonenPublished
2018
Frank Michael Schleif, Andrej Gisbrecht, Peter Tino (2018). Supervised low rank indefinite kernel approximation using minimum enclosing balls. NEUROCOMPUTING, 318:213-226. [Link]
Supervised low rank indefinite kernel approximation using minimum enclosing ballsSchleifPublished
Submitted
Zheyang Shen, Markus Heinonen, Samuel Kaski (2018). Harmonizable mixture kernels with variational Fourier features. [Preprint]
Harmonizable mixture kernels with variational Fourier featuresShenSubmitted
To appear
Eero Siivola, Aki Vehtari, Jarno Vanhatalo, Javier Gonzalez , Michael Andersen (2018). Correcting boundary over-exploration deficiencies in Bayesian optimization with virtual derivative sign observations. IEEE International Workshop on Machine Learning for Signal Processing, 2018 IEEE International Workshop on Machine Learning for Signal Processing. [Preprint]
Correcting boundary over-exploration deficiencies in Bayesian optimization with virtual derivative sign observationsSiivolaAccepted/In press
2018
Pilleriin Sikka, Henri Pesonen, Antti Revonsuo (2018). Peace of mind and anxiety in the waking state are related to the affective content of dreams. SCIENTIFIC REPORTS, 8(1):1-13. [Link]
Peace of mind and anxiety in the waking state are related to the affective content of dreamsSikkaPublished
2018
Jeff Sperinde, Weidong Huang, Aki Vehtari, Ahmed Chenna, Pirkko Liisa Kellokumpu-Lehtinen, John Winslow, Petri Bono, Yolanda S. Lie, Christos J. Petropoulos, Jodi Weidler, Heikki Joensuu (2018). P95HER2 methionine 611 carboxy-terminal fragment is predictive of trastuzumab adjuvant treatment benefit in the fin her trial. CLINICAL CANCER RESEARCH, 24(13):3046-3052. [Link]
P95HER2 methionine 611 carboxy-terminal fragment is predictive of trastuzumab adjuvant treatment benefit in the fin her trialSperindePublished
2018
Iiris Sundin, Tomi Peltola, Luana Micallef, Homayun Afrabandpey, Marta Soare, Muntasir Mamun Majumder, Pedram Daee, Chen He, Bariş Serim, Aki Havulinna, Caroline Heckman, Giulio Jacucci, Pekka Marttinen, Samuel Kaski (2018). Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge. BIOINFORMATICS, 34(13):i395-i403. [Link]
Improving genomics-based predictions for precision medicine through active elicitation of expert knowledgeSundinPublished
2018
Kei Ichiro Takahashi, David A. duVerle, Sohiya Yotsukura, Ichigaku Takigawa, Hiroshi Mamitsuka (2018). SiBIC A tool for generating a network of biclusters captured by maximal frequent itemset mining. Methods in Molecular Biology, Methods in Molecular Biology, 1807:95-111. [Link]
SiBIC A tool for generating a network of biclusters captured by maximal frequent itemset miningTakahashiPublished
2018
Kishan Wimalawarne, Makoto Yamada, Hiroshi Mamitsuka (2018). Convex Coupled Matrix and tensor completion. NEURAL COMPUTATION, 30(11):3095-3127. [Link]
Convex Coupled Matrix and tensor completionWimalawarnePublished
2018
Ronghui You, Zihan Zhang, Yi Xiong, Fengzhu Sun, Hiroshi Mamitsuka, Shanfeng Zhu (2018). GOLabeler improving sequence-based large-scale protein function prediction by learning to rank. BIOINFORMATICS, 34(14):2465-2473. [Link]
GOLabeler improving sequence-based large-scale protein function prediction by learning to rankYouPublished
2017
Homayun Afrabandpey, Tomi Peltola, Samuel Kaski (2017). Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction. Conference on User Modeling, Adaptation and Personalization, Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, p. 265-269. [preprint] [Link]
Interactive Prior Elicitation of Feature Similarities for Small Sample Size PredictionAfrabandpeyPublished
2017
Muhammad Ammad-ud-din (2017). Machine learning methods for improving drug response prediction in cancer. [Link]
Machine learning methods for improving drug response prediction in cancerAmmad-ud-dinPublished
2017
Muhammad Ammad-Ud-Din, Suleiman A. Khan, Krister Wennerberg, Tero Aittokallio (2017). Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression. BIOINFORMATICS, 33(14):i359-i368. [Link]
Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regressionAmmad-Ud-DinPublished
2017
Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen (2017). Bayesian inference for spatio-temporal spike-and-slab priors. JOURNAL OF MACHINE LEARNING RESEARCH, 18:1-58.
Bayesian inference for spatio-temporal spike-and-slab priorsAndersenPublished
2017
Kumaripaba Athukorala, Luana Micallef, Chao An, Aki Reijonen, Jaakko Peltonen, Tuukka Ruotsalo, Giulio Jacucci (2017). Visualizing activity traces to support collaborative literature searching. Symposium on Visual Information Communication and Interaction, VINCI 2017 - 10th International Symposium on Visual Information Communication and Interaction, p. 45-52. [Link]
Visualizing activity traces to support collaborative literature searchingAthukoralaPublished
2017
Chloé Agathe Azencott, Tero Aittokallio, Sushmita Roy, Thea Norman, Stephen Friend, Gustavo Stolovitzky, Anna Goldenberg, Ankit Agrawal, Emmanuel Barillot, Nikolai Bessonov, Deborah Chasman, Urszula Czerwinska, Alireza Fotuhi Siahpirani, Jan Greenberg, Manuel Huber, Samuel Kaski, Christoph Kurz, Marsha Mailick, Michael Merzenich, Nadya Morozova, Arezoo Movaghar, Mor Nahum, Torbjörn E.M. Nordling, Robert Penner, Krishanu Saha, Asif Salim, Siamak Sorooshyari, Vassili Soumelis, Alit Stark-Inbar, Audra Sterling, S. S. Shiju, Jing Tang, Alen Tosenberger, Thomas Van Vieet, Krister Wennerberg, Andrey Zinovyev (2017). The inconvenience of data of convenience Computational research beyond post-mortem analyses. NATURE METHODS, 14(10):937-938. [Link]
The inconvenience of data of convenience Computational research beyond post-mortem analysesAzencottPublished
2017
Sahely Bhadra, Samuel Kaski, Juho Rousu (2017). Multi-view kernel completion. MACHINE LEARNING, 106(5):713–739. [Link]
Multi-view kernel completionBhadraPublished
2017
Rita Borgo, Bongshin Lee, Benjamin Bach, Sara Fabrikant, Radu Jianu, Andreas Kerren, Stephen Kobourov, Fintan McGee, Luana Micallef, Tatiana von Landesberger, Katrin Ballweg, Stephan Diehl, Paolo Simonetto, Michelle Zhou (2017). Crowdsourcing for Information Visualization: Promises and Pitfalls. Lecture Notes in Computer Science, Evaluation in the Crowd: Crowdsourcing and Human-Centered Experiments Dagstuhl Seminar 15481, Dagstuhl Castle, Germany, November 22 – 27, 2015 Revised Contributions, 10264:96-138. [Link]
Crowdsourcing for Information Visualization: Promises and PitfallsBorgoPublished
2017
Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski (2017). Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction. MACHINE LEARNING, 106(9):1599-1620. [Code and data] [Link]
Knowledge elicitation via sequential probabilistic inference for high-dimensional predictionDaeePublished
2017
Sophia David, Leonor Sánchez-Busó, Simon R Harris, Pekka Marttinen, Christophe Rusniok, Carmen Buchrieser, Timothy G. Harrison, Julian Parkhill (2017). Dynamics and impact of homologous recombination on the evolution of Legionella pneumophila. PLOS GENETICS, 13(6):1-21. [Link]
Dynamics and impact of homologous recombination on the evolution of Legionella pneumophilaDavidPublished
Submitted
Ritabrata Dutta, Jukka Corander, Samuel Kaski, Michael Gutmann (2017). Likelihood-free inference by ratio estimation. [Preprint]
Likelihood-free inference by ratio estimationDuttaSubmitted
2017
Andrew Gelman, Aki Vehtari (2017). Comment Consensus Monte Carlo using expectation propagation. BRAZILIAN JOURNAL OF PROBABILITY AND STATISTICS, 31(4):692-696. [Link]
Comment Consensus Monte Carlo using expectation propagationGelmanPublished
Submitted
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. [Preprint]
Expectation propagation as a way of life: A framework for Bayesian inference on partitioned dataGelmanSubmitted
2017
Jussi Gillberg, Pekka Marttinen, Hiroshi Mamitsuka, Samuel Kaski (2017). Modelling G×E with historical weather information improves genomic prediction in new environments. bioRxiv, p. 1-12. [Link]
Modelling G×E with historical weather information improves genomic prediction in new environmentsGillbergPublished
2017
Mehmet Gönen, Barbara A. Weir, Glenn S. Cowley, Francisca Vazquez, Yuanfang Guan, Alok Jaiswal, Masayuki Karasuyama, Vladislav Uzunangelov, Tao Wang, Aviad Tsherniak, Sara Howell, Daniel Marbach, Bruce Hoff, Thea C. Norman, Antti Airola, Adrian Bivol, Kerstin Bunte, Daniel Carlin, Sahil Chopra, Alden Deran, Kyle Ellrott, Peddinti Gopalacharyulu, Kiley Graim, Samuel Kaski, Suleiman A. Khan, Yulia Newton, Sam Ng, Tapio Pahikkala, Evan Paull, Artem Sokolov, Hao Tang, Jing Tang, Krister Wennerberg, Yang Xie, Xiaowei Zhan, Fan Zhu, Tero Aittokallio, Hiroshi Mamitsuka, Joshua M. Stuart, Jesse S. Boehm, David E. Root, Guanghua Xiao, Gustavo Stolovitzky, William C. Hahn, Adam A. Margolin (2017). A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines. Cell Systems, 5(5):485-497. [Link]
A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell LinesGönenPublished
2017
Chen He, Luana Micallef, Zia-Ur-Rehman Tanoli, Samuel Kaski, Tero Aittokallio, Giulio Jacucci (2017). MediSyn Uncertainty-aware Visualization of Multiple Biomedical Datasets to Support Drug Treatment Selection. Symposium on Biological Data Visualization, BMC BIOINFORMATICS, 18:1-12. [Link]
MediSyn Uncertainty-aware Visualization of Multiple Biomedical Datasets to Support Drug Treatment SelectionHePublished
2017
Mikko Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela (2017). Differentially Private Bayesian Learning on Distributed Data. ANNUAL CONFERENCE ON NEURAL INFORMATION PROCESSING SYSTEMS, Advances in Neural Information Processing Systems, Advances in Neural Information Processing Systems 30 Proceedings of NIPS 2017, 30:3227-3236. [Preprint] [Pre-Proceedings]
Differentially Private Bayesian Learning on Distributed DataHeikkiläPublished
2017
Marko Järvenpää, Michael Gutmann, Aki Vehtari, Pekka Marttinen (2017). Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria.
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteriaJärvenpääPublished
2017
Marko Järvenpää, Michael Gutmann, Arijus Pleska, Aki Vehtari, Pekka Marttinen (2017). Efficient acquisition rules for model-based approximate Bayesian computation. [Preprint]
Efficient acquisition rules for model-based approximate Bayesian computationJärvenpääPublished
To appear
Antti Kangasrääsiö, Samuel Kaski (2017). Modelling Human Decision-making based on Aggregate Observation Data. Human In The Loop-ML Workshop at ICML [Workshop web page] [Link]
Modelling Human Decision-making based on Aggregate Observation DataKangasrääsiöAccepted/In press
2017
Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta (2017). Inferring Cognitive Models from Data using Approximate Bayesian Computation. ACM SIGCHI CONFERENCE ON HUMAN FACTORS IN COMPUTING SYSTEMS, Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, p. 1295-1306. [Link]
Inferring Cognitive Models from Data using Approximate Bayesian ComputationKangasrääsiöPublished
2017
Antti Kangasrääsiö, Samuel Kaski (2017). Inference of Strategic Behavior based on Incomplete Observation Data. Neural Information Processing Systems, NIPS17 Workshop: Learning in the Presence of Strategic Behavior, [Workshop home page]
Inference of Strategic Behavior based on Incomplete Observation DataKangasrääsiöPublished
2017
Khalil Klouche, Tuukka Ruotsalo, Luana Micallef, Salvatore Andolina, Giulio Jacucci (2017). Visual Re-Ranking for Multi-Aspect Information Retrieval. Conference on Human Information Interaction and Retrieval, CHIIR 2017 - Proceedings of the 2017 Conference Human Information Interaction and Retrieval, p. 57-66. [Link]
Visual Re-Ranking for Multi-Aspect Information RetrievalKlouchePublished
2017
Pekka Kohonen, Juuso A. Parkkinen, Egon L. Willighagen, Rebecca Ceder, Krister Wennerberg, Samuel Kaski, Roland C. Grafström (2017). A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury. NATURE COMMUNICATIONS, 8:1-15. [Link]
A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injuryKohonenPublished
2017
Olli-Pekka Koistinen, Freyja B. Dagbjartsdóttir, Vilhjálmur Ásgeirsson, Aki Vehtari, Hannes Jonsson (2017). Nudged elastic band calculations accelerated with Gaussian process regression. JOURNAL OF CHEMICAL PHYSICS, 147(15):1-14. [Preprint] [Link]
Nudged elastic band calculations accelerated with Gaussian process regressionKoistinenPublished
2017
Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski (2017). GFA Exploratory Analysis of Multiple Data Sources with Group Factor Analysis. JOURNAL OF MACHINE LEARNING RESEARCH, 18:1-5. [Link]
GFA Exploratory Analysis of Multiple Data Sources with Group Factor AnalysisLeppäahoPublished
2017
Ziyuan Lin, Jaakko Peltonen (2017). An Information Retrieval Approach for Finding Dependent Subspaces of Multiple Views. International Conference on Machine Learning and Data Mining, Lecture Notes in Computer Science, Machine Learning and Data Mining in Pattern Recognition 13th International Conference, MLDM 2017 New York, NY, USA, July 15 – 20, 2017, Proceedings, p. 1-16. [Link]
An Information Retrieval Approach for Finding Dependent Subspaces of Multiple ViewsLinPublished
Submitted
Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skyten, Marko Järvenpää, Michael Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski (2017). ELFI Engine for likelihood-free inference. [Code] [Documentation] [Preprint]
ELFI Engine for likelihood-free inferenceLintusaariSubmitted
2017
Jarno Lintusaari, Paul Blomstedt, Tuomas Sivula, Michael U. Gutmann, Samuel Kaski, Jukka Corander (2017). Resolving outbreak dynamics using Approximate Bayesian Computation for stochastic birth-death models. bioRxiv, [Link]
Resolving outbreak dynamics using Approximate Bayesian Computation for stochastic birth-death modelsLintusaariPublished
2017
Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skyten, Marko Järvenpää, Michael Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski (2017). ELFI, a software package for likelihood-free inference. International Conference on Machine Learning,
ELFI, a software package for likelihood-free inferenceLintusaariPublished
2017
Pekka Marttinen, William P. Hanage (2017). Speciation trajectories in recombining bacterial species. PLOS COMPUTATIONAL BIOLOGY, 13(7):1-15. [Link]
Speciation trajectories in recombining bacterial speciesMarttinenPublished
2017
Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-Ud-Din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski (2017). Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. International Conference on Intelligent User Interfaces, IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces, p. 547-552. [preprint] [Link]
Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data SetsMicallefPublished
2017
Luana Micallef, Gregorio Palmas, Antti Oulasvirta, Tino Weinkauf (2017). Towards Perceptual Optimization of the Visual Design of Scatterplots. IEEE Pacific Visualization Symposium, IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 23(6):1588-1599. [Link]
Towards Perceptual Optimization of the Visual Design of ScatterplotsMicallefPublished
2017
Rafal Mostowy, Nicholas J. Croucher, Cheryl P. Andam, Jukka Corander, William P Hanage, Pekka Marttinen (2017). Efficient Inference of Recent and Ancestral Recombination within Bacterial Populations. MOLECULAR BIOLOGY AND EVOLUTION, 34(5):1167-1182. [Link]
Efficient Inference of Recent and Ancestral Recombination within Bacterial PopulationsMostowyPublished
2017
Pekka Parviainen, Samuel Kaski (2017). Learning structures of Bayesian networks for variable groups. INTERNATIONAL JOURNAL OF APPROXIMATE REASONING, 88:110-127. [preprint] [Link]
Learning structures of Bayesian networks for variable groupsParviainenPublished
2017
Jaakko Peltonen, Jonathan Strahl, Patrik Floréen (2017). Negative relevance feedback for exploratory search with visual interactive intent modeling. International Conference on Intelligent User Interfaces, IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces, p. 149-159. [Link]
Negative relevance feedback for exploratory search with visual interactive intent modelingPeltonenPublished
2017
Jaakko Peltonen, Kseniia Belorustceva, Tuukka Ruotsalo (2017). Improving search result comprehension by topic-relevance map visualization. International Conference on Intelligent User Interfaces, IUI 2017 - Companion of the 22nd International Conference on Intelligent User Interfaces, p. 149-152. [Link]
Improving search result comprehension by topic-relevance map visualizationPeltonenPublished
2017
Jaakko Peltonen, Ziyuan Lin (2017). Parallel coordinate plots for neighbor retrieval. International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, 3:40-51.
Parallel coordinate plots for neighbor retrievalPeltonenPublished
2017
Jaakko Peltonen, Kseniia Belorustceva, Tuukka Ruotsalo (2017). Topic-relevance map Visualization for improving search result comprehension. International Conference on Intelligent User Interfaces, IUI 2017 - Proceedings of the 22nd International Conference on Intelligent User Interfaces, p. 611-622. [Link]
Topic-relevance map Visualization for improving search result comprehensionPeltonenPublished
2017
Juho Piironen, Aki Vehtari (2017). On the hyperprior choice for the global shrinkage parameter in the horseshoe prior. International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 54. [Link]
On the hyperprior choice for the global shrinkage parameter in the horseshoe priorPiironenPublished
2017
Juho Piironen, Aki Vehtari (2017). Comparison of Bayesian predictive methods for model selection. STATISTICS AND COMPUTING, 27(3):711-735. [Link]
Comparison of Bayesian predictive methods for model selectionPiironenPublished
2017
Juho Piironen, Aki Vehtari (2017). Sparsity information and regularization in the horseshoe and other shrinkage priors. ELECTRONIC JOURNAL OF STATISTICS, 11(2):5018-5051. [Link]
Sparsity information and regularization in the horseshoe and other shrinkage priorsPiironenPublished
2017
Matti Pirinen, Christian Benner, Pekka Marttinen, Marjo-Riitta Järvelin, Manuel A Rivas, Samuli Ripatti (2017). biMM: efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurements. BIOINFORMATICS, 33(15):2405-2407. [Link]
biMM: efficient estimation of genetic variances and covariances for cohorts with high-dimensional phenotype measurementsPirinenPublished
2017
Ilya Potapov, Marko Järvenpää, Markku Åkerblom, Pasi Raumonen, Mikko Kaasalainen (2017). Bayes Forest A data-intensive generator of morphological tree clones. GigaScience, 6(10):1-13. [Link]
Bayes Forest A data-intensive generator of morphological tree clonesPotapovPublished
2017
Olli Pekka Pulkka, Bengt Nilsson, Maarit Sarlomo-Rikala, Peter Reichardt, Mikael Eriksson, Kirsten Sundby Hall, Eva Wardelmann, Aki Vehtari, Heikki Joensuu, Harri Sihto (2017). SLUG transcription factor A pro-survival and prognostic factor in gastrointestinal stromal tumour. BRITISH JOURNAL OF CANCER, 116(9):1195-1202. [Link]
SLUG transcription factor A pro-survival and prognostic factor in gastrointestinal stromal tumourPulkkaPublished
Submitted
Xiangju Qin, Paul Blomstedt, Eemeli Leppäaho, Pekka Parviainen, Samuel Kaski (2017). Distributed Bayesian Matrix Factorization with Minimal Communication. [Preprint]
Distributed Bayesian Matrix Factorization with Minimal CommunicationQinSubmitted
2017
Sami Remes, Markus Heinonen, Samuel Kaski (2017). A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings. Asian Conference on Machine Learning, Proceedings of Machine Learning Research, Proceedings of the 9th Asian Conference on Machine Learning, 77:455-470. [Link] [Preprint] [Code]
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable CouplingsRemesPublished
2017
Sami Remes, Markus Heinonen, Samuel Kaski (2017). Non-Stationary Spectral Kernels. NIPS Symposium on Interpretable Machine Learning, Advances in Neural Information Processing Systems, Advances in Neural Information Processing Systems 30 Proceedings of NIPS2017, 30:4645-4654. [Preprint]
Non-Stationary Spectral KernelsRemesPublished
2017
Tuukka Ruotsalo, Jaakko Peltonen, Manuel Eugster, Petri Myllymäki, Giulio Jacucci, Samuel Kaski, Dorota Glowacka (2017). Low-dimensional information discovery and presentation system, apparatus and method.
Low-dimensional information discovery and presentation system, apparatus and methodRuotsaloPublished
2017
Dominik Sacha, Michael Sedlmair, Leishi Zhang, John A. Lee, Jaakko Peltonen, Daniel Weiskopf, Stephen C. North, Daniel A. Keim (2017). What you see is what you can change Human-centered machine learning by interactive visualization. NEUROCOMPUTING, 268:164-175. [Link]
What you see is what you can change Human-centered machine learning by interactive visualizationSachaPublished
2017
Juha Salmi, Olli-Pekka Koistinen, Enrico Glerean, Pasi Jylänki, Aki Vehtari, Iiro Jääskeläinen, Sasu Mäkelä, Lauri Nummenmaa, Katarina Nummi-Kuisma, Ilari Nummi, Mikko Sams (2017). Distributed neural signatures of natural audiovisual speech and music in the human auditory cortex. NEUROIMAGE, 157:108-117. [Link] [Link]
Distributed neural signatures of natural audiovisual speech and music in the human auditory cortexSalmiPublished
2017
K. Santalahti, A. Havulinna, M. Maksimow, T. Zeller, S. Blankenberg, A. Vehtari, H. Joensuu, S. Jalkanen, V. Salomaa, M. Salmi (2017). Plasma levels of hepatocyte growth factor and placental growth factor predict mortality in a general population a prospective cohort study. JOURNAL OF INTERNAL MEDICINE, 282(4):340-352. [Link]
Plasma levels of hepatocyte growth factor and placental growth factor predict mortality in a general population a prospective cohort studySantalahtiPublished
2017
Dmitry Smirnov, Fanny Lachat, Tomi Peltola, Juha Lahnakoski, Olli-Pekka Koistinen, Enrico Glerean, Aki Vehtari, Riitta Hari, Mikko Sams, Lauri Nummenmaa (2017). Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humans. PLOS ONE, 12(12). [Link]
Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humansSmirnovPublished
2017
Marta Soare, Muhammad Ammad-Ud-din, Samuel Kaski (2017). Regression with n → 1 by expert knowledge elicitation. IEEE International Conference on Machine Learning and Applications, Proceedings - 2016 15th IEEE International Conference on Machine Learning and Applications, ICMLA 2016, p. 734-739. [Link]
Regression with n → 1 by expert knowledge elicitationSoarePublished
2017
Topi Talvitie, Teppo Niinimäki, Mikko Koivisto (2017). The Mixing of Markov Chains on Linear Extensions in Practice. International Joint Conference on Artificial Intelligence, Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence (IJCAI-17), p. 524-530. [Link] [Link]
The Mixing of Markov Chains on Linear Extensions in PracticeTalvitiePublished
2017
Santosh Tirunagari, Simon C. Bull, Aki Vehtari, Christopher Farmer, Simon De Lusignan, Norman Poh (2017). Automatic detection of acute kidney injury episodes from primary care data. IEEE Symposium Series on Computational Intelligence, 2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, [Link]
Automatic detection of acute kidney injury episodes from primary care dataTirunagariPublished
2017
Pia M. Villa, Pekka Marttinen, Jussi Gillberg, A. Inkeri Lokki, Kerttu Majander, Maija Riitta Ordén, Pekka Taipale, Anukatriina Pesonen, Katri Räikkönen, Esa Hämäläinen, Eero Kajantie, Hannele Laivuori (2017). Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) study. PLOS ONE, 12(3):1-14. [Link]
Cluster analysis to estimate the risk of preeclampsia in the high-risk Prediction and Prevention of Preeclampsia and Intrauterine Growth Restriction (PREDO) studyVillaPublished
2017
Makoto Yamada, Wenzhao Lian, Amit Goyal, Jianhui Chen, Kishan Wimalawarne, Suleiman A. Khan, Samuel Kaski, Hiroshi Mamitsuka, Yi Chang (2017). Convex factorization machine for toxicogenomics prediction. International Conference on Knowledge Discovery and Data Mining, KDD 2017 - Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, p. 1215-1224. [Link]
Convex factorization machine for toxicogenomics predictionYamadaPublished
2017
Makoto Yamada, Takeuchi Koh, Tomoharu Iwata, John Shawe-Taylor, Samuel Kaski (2017). Localized Lasso for High-Dimensional Regression. International Conference on Artificial Intelligence and Statistics, Proceedings of Machine Learning Research, Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 54:325-333. [Link]
Localized Lasso for High-Dimensional RegressionYamadaPublished
Submitted
Yuling Yao, Aki Vehtari, Daniel Simpson, Andrew Gelman (2017). Using stacking to average Bayesian predictive distributions. [Preprint]
Using stacking to average Bayesian predictive distributionsYaoSubmitted
2016
Klaus Harms, Asbjørn Lunnan, Nils Hülter, Tobias Mourier, Lasse Vinner, Cheryl P. Andam, Pekka Marttinen, Helena Fridholm, Anders Johannes Hansen, William P. Hanage, Kaare Magne Nielsen, Eske Willerslev, Pal Jarle Johnsen (2016). Substitutions of short heterologous DNA segments of intragenomic or extragenomic origins produce clustered genomic polymorphisms. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 113(52):15066-15071. [Link]
Substitutions of short heterologous DNA segments of intragenomic or extragenomic origins produce clustered genomic polymorphismsHarmsPublished
2016
Markus Heinonen, Emmi Jokinen, Samuel Kaski, Juho Rousu, Harri Lähdesmäki (2016). Generating data to improve protein stability prediction.
Generating data to improve protein stability predictionHeinonenPublished
2016
Juho Piironen, Aki Vehtari (2016). Projection predictive model selection for Gaussian processes. IEEE International Workshop on Machine Learning for Signal Processing, IEEE International Workshop on Machine Learning for Signal Processing, 2016 IEEE 26th International Workshop on Machine Learning for Signal Processing (MLSP), [Link]
Projection predictive model selection for Gaussian processesPiironenPublished
2016
Sami Remes, Tommi Mononen, Samuel Kaski (2016). Classification of weak multi-view signals by sharing factors in a mixture of Bayesian group factor analyzers. Workshop on Machine Learning and Interpretation in Neuroimaging, Proceedings of the 5th Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI) at NIPS 2015, [Proceedings of the 5th Workshop on Machine Learning and Interpretation in Neuroimaging (MLINI) at NIPS 2015]
Classification of weak multi-view signals by sharing factors in a mixture of Bayesian group factor analyzersRemesPublished
2016
Sohan Seth, Manuel J A Eugster (2016). Archetypal Analysis for Nominal Observations. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 38(5):849-861. [Link]
Archetypal Analysis for Nominal ObservationsSethPublished
Submitted
Eero Siivola, Juho Piironen, Aki Vehtari (2016). Automatic monotonicity detection for Gaussian Processes. [Preprint]
Automatic monotonicity detection for Gaussian ProcessesSiivolaSubmitted
Submitted
Aki Vehtari, Andrew Gelman, Jonah Gabry (2016). Pareto Smoothed Importance Sampling. [Preprint]
Pareto Smoothed Importance SamplingVehtariSubmitted
2016
Sebastian Weber, Andrew Gelman, Bob Carpenter, Daniel Lee, Michael Betancourt, Aki Vehtari, Amy Racine (2016). Hierarchical expectation propagation for Bayesian aggregation of average data.
Hierarchical expectation propagation for Bayesian aggregation of average dataWeberPublished

2016

2015

2014 and earlier

Publications of the former Statistical Machine Learning and Bioinformatics group


Publications of the former Bayesian Methodology group



This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.