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
2017
Homayun Afrabandpey, Tomi Peltola, Samuel Kaski (2017). Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction. ACM International Conference on User Modeling, Adaptation, and Personalization, Proceedings of the 25th Conference on User Modeling, Adaptation and Personalization, p. 265-269. [Link]
Interactive Prior Elicitation of Feature Similarities for Small Sample Size PredictionAfrabandpeyPublished
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
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.
Crowdsourcing for Information Visualization: Promises and PitfallsBorgoPublished
Submitted
Pedram Daee, Tomi Peltola, Aki Vehtari, Samuel Kaski (2017). User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. [Preprint]
User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for PredictionDaeeSubmitted
2017
Pedram Daee, Tomi Peltola, Marta Soare, Samuel Kaski (2017). Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction. MACHINE LEARNING, p. 1-22. [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, Paul Blomstedt, Samuel Kaski (2017). Bayesian inference in hierarchical models by combining independent posteriors.
Bayesian inference in hierarchical models by combining independent posteriorsDuttaSubmitted
Submitted
Ritabrata Dutta, Jukka Corander, Samuel Kaski, Michael Gutmann (2017). Likelihood-free inference by penalised logistic regression.
Likelihood-free inference by penalised logistic regressionDuttaSubmitted
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
To appear
Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander (2017). Likelihood-free inference via classification. STATISTICS AND COMPUTING. [Link]
Likelihood-free inference via classificationGutmannE-pub ahead of print
To appear
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. [Link]
A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell LinesGönenE-pub ahead of print
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
Submitted
Mikko Heikkilä, Eemil Lagerspetz, Samuel Kaski, Kana Shimizu, Sasu Tarkoma, Antti Honkela (2017). Differentially Private Bayesian Learning on Distributed Data. [Preprint]
Differentially Private Bayesian Learning on Distributed DataHeikkiläSubmitted
Submitted
Antti Honkela, Mrinal Das, Arttu Nieminen, Onur Dikmen, Samuel Kaski (2017). Efficient differentially private learning improves drug sensitivity prediction. [Preprint]
Efficient differentially private learning improves drug sensitivity predictionHonkelaSubmitted
Submitted
Marko Järvenpää, Michael Gutmann, Aki Vehtari, Pekka Marttinen (2017). Efficient acquisition rules for model-based approximate Bayesian computation.
Efficient acquisition rules for model-based approximate Bayesian computationJärvenpääSubmitted
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 annual 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
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]
Modelling Human Decision-making based on Aggregate Observation DataKangasrääsiöAccepted/In press
Submitted
Antti Kangasrääsiö, Samuel Kaski (2017). Inverse Reinforcement Learning from Summary Data. [ArXiv preprint]
Inverse Reinforcement Learning from Summary DataKangasrääsiöSubmitted
2017
Khalil Klouche, Tuukka Ruotsalo, Luana Micallef, Salvatore Andolina, Giulio Jacucci (2017). Visual Re-Ranking for Multi-Aspect Information Retrieval. ACM SIGIR 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 Artificial Intelligence, Machine Learning and Data Mining in Pattern Recognition 13th International Conference, MLDM 2017 New York, NY, USA, July 15 – 20, 2017, Proceedings, 10358:1-16. [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. [Preprint] [Code] [Documentation]
ELFI: Engine for Likelihood-Free InferenceLintusaariSubmitted
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, Part F126745:547-552. [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. [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, Part F126746:149-152. [Link]
Improving search result comprehension by topic-relevance map visualizationPeltonenPublished
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, Part F126745:611-622. [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.
On the hyperprior choice for the global shrinkage parameter in the horseshoe priorPiironenPublished
Submitted
Juho Piironen, Aki Vehtari (2017). Sparsity information and regularization in the horseshoe and other shrinkage priors. [Preprint]
Sparsity information and regularization in the horseshoe and other shrinkage priorsPiironenSubmitted
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
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
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
To appear
Sami Remes, Markus Heinonen, Samuel Kaski (2017). A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings. ACML [Preprint]
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable CouplingsRemesAccepted/In press
To appear
Sami Remes, Markus Heinonen, Samuel Kaski (2017). Non-Stationary Spectral Kernels. NIPS [Preprint]
Non-Stationary Spectral KernelsRemesAccepted/In press
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
Submitted
Eero Siivola, Aki Vehtari, Jarno Vanhatalo, Javier Gonzalez (2017). Bayesian optimization with virtual derivative sign observations.
Bayesian optimization with virtual derivative sign observationsSiivolaSubmitted
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
Submitted
Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder, Pedram Daee, Marta Soare, Homayun Afrabandpey, Caroline Heckman, Samuel Kaski, Pekka Marttinen (2017). Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation. [Preprint]
Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitationSundinSubmitted
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, Part F129685:1215-1224. [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.
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
Submitted
Marko Järvenpää, Michael Gutmann, Aki Vehtari, Pekka Marttinen (2016). 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 bacteriaJärvenpääSubmitted
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.
Automatic monotonicity detection for Gaussian ProcessesSiivolaSubmitted
Submitted
Aki Vehtari, Andrew Gelman, Jonah Gabry (2016). Pareto Smoothed Importance Sampling.
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
Submitted
Michael Riis Andersen, Aki Vehtari, Ole Winther, Lars Kai Hansen (2015). Bayesian inference for spatio-temporal spike and slab priors.
Bayesian inference for spatio-temporal spike and slab priorsAndersenSubmitted
Submitted
Dmitry Smirnov, Fanny Lachat, Tomi Peltola, Juha Lahnakoski, Olli-Pekka Koistinen, Enrico Glerean, Aki Vehtari, Riitta Hari, Mikko Sams, Lauri Nummenmaa (2015). Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humans.
Brain-to-brain hyperclassification reveals action-specific motor mapping of observed actions in humansSmirnovSubmitted

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.