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Medical Code Assignment with Gated Convolution and Note-Code Interaction

Oct 14, 2020
Shaoxiong Ji, Shirui Pan, Pekka Marttinen


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Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text

Sep 30, 2020
Shaoxiong Ji, Erik Cambria, Pekka Marttinen

* The 3rd Clinical Natural Language Processing Workshop at EMNLP 2020 

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Informative Gaussian Scale Mixture Priors for Bayesian Neural Networks

Feb 24, 2020
Tianyu Cui, Aki Havulinna, Pekka Marttinen, Samuel Kaski


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A Survey on Knowledge Graphs: Representation, Acquisition and Applications

Feb 02, 2020
Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu

* 25 pages, 10 figures, 9 tables 

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Batch simulations and uncertainty quantification in Gaussian process surrogate-based approximate Bayesian computation

Oct 14, 2019
Marko Järvenpää, Aki Vehtari, Pekka Marttinen


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Errors-in-variables Modeling of Personalized Treatment-Response Trajectories

Jun 10, 2019
Guangyi Zhang, Reza Ashrafi, Anne Juuti, Kirsi Pietiläinen, Pekka Marttinen


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Parallel Gaussian process surrogate method to accelerate likelihood-free inference

May 03, 2019
Marko Järvenpää, Michael Gutmann, Aki Vehtari, Pekka Marttinen

* 35 pages, 15 figures 

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Recovering Pairwise Interactions Using Neural Networks

Jan 24, 2019
Tianyu Cui, Pekka Marttinen, Samuel Kaski


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A Bayesian model of acquisition and clearance of bacterial colonization

Nov 27, 2018
Marko Järvenpää, Mohamad R. Abdul Sater, Georgia K. Lagoudas, Paul C. Blainey, Loren G. Miller, James A. McKinnell, Susan S. Huang, Yonatan H. Grad, Pekka Marttinen

* Machine Learning for Health (ML4H) Workshop at NeurIPS 2018 arXiv:1811.07216 

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Efficient acquisition rules for model-based approximate Bayesian computation

Aug 08, 2018
Marko Järvenpää, Michael U. Gutmann, Arijus Pleska, Aki Vehtari, Pekka Marttinen

* 30 pages, 10 figures 

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ELFI: Engine for Likelihood-Free Inference

Jul 05, 2018
Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski

* Journal of Machine Learning Research, 19(16):1-7, 2018. http://jmlr.org/papers/v19/17-374.html 

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Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria

Feb 16, 2018
Marko Järvenpää, Michael Gutmann, Aki Vehtari, Pekka Marttinen

* 25 pages, 11 figures 

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Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation

May 09, 2017
Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder, Pedram Daee, Marta Soare, Homayun Afrabandpey, Caroline Heckman, Samuel Kaski, Pekka Marttinen

* 24 pages, 3 figures 

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Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets

Jan 16, 2017
Luana Micallef, Iiris Sundin, Pekka Marttinen, Muhammad Ammad-ud-din, Tomi Peltola, Marta Soare, Giulio Jacucci, Samuel Kaski

* in Proceedings of the 22nd International Conference on Intelligent User Interfaces (IUI 2017) 

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Multiple Output Regression with Latent Noise

Feb 03, 2016
Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J. Kangas, Pasi Soininen, Mehreen Ali, Aki S. Havulinna, Marjo-Riitta Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski


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Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects

Oct 16, 2013
Jussi Gillberg, Pekka Marttinen, Matti Pirinen, Antti J Kangas, Pasi Soininen, Marjo-Riitta Järvelin, Mika Ala-Korpela, Samuel Kaski


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