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T-SNE Is Not Optimized to Reveal Clusters in Data


Oct 06, 2021
Zhirong Yang, Yuwei Chen, Jukka Corander

* arXiv admin note: text overlap with arXiv:2108.08003 

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Stochastic Cluster Embedding


Aug 18, 2021
Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander


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Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC


Apr 08, 2021
Marko Järvenpää, Jukka Corander


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Structure Learning of Contextual Markov Networks using Marginal Pseudo-likelihood


Mar 29, 2021
Johan Pensar, Henrik Nyman, Jukka Corander

* Scandinavian Journal of Statistics, Vol. 44: 455-479, 2017 

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Likelihood-Free Inference with Deep Gaussian Processes


Jun 18, 2020
Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski


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Split-BOLFI for for misspecification-robust likelihood free inference in high dimensions


Feb 21, 2020
Owen Thomas, Henri Pesonen, Raquel Sá-Leão, Hermínia de Lencastre, Samuel Kaski, Jukka Corander


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Diagnosing model misspecification and performing generalized Bayes' updates via probabilistic classifiers


Dec 12, 2019
Owen Thomas, Jukka Corander


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Learning pairwise Markov network structures using correlation neighborhoods


Oct 30, 2019
Juri Kuronen, Jukka Corander, Johan Pensar


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High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study


Jan 14, 2019
Johan Pensar, Yingying Xu, Santeri Puranen, Maiju Pesonen, Yoshiyuki Kabashima, Jukka Corander


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Doubly Stochastic Neighbor Embedding on Spheres


Sep 11, 2018
Yao Lu, Jukka Corander, Zhirong Yang


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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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Likelihood-free inference by ratio estimation


Aug 21, 2017
Ritabrata Dutta, Jukka Corander, Samuel Kaski, Michael U. Gutmann


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Likelihood-free inference via classification


Mar 03, 2017
Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander

* Accepted for publication in Statistics and Computing (Feb 13, 2017) 

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Inferring Cognitive Models from Data using Approximate Bayesian Computation


Jan 13, 2017
Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta

* To appear in CHI'2017 

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Fast k-NN search


Aug 19, 2016
Ville Hyvönen, Teemu Pitkänen, Sotiris Tasoulis, Elias Jääsaari, Risto Tuomainen, Liang Wang, Jukka Corander, Teemu Roos


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On the inconsistency of $\ell_1$-penalised sparse precision matrix estimation


Mar 08, 2016
Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela

* 9 pages, 10 figures 

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Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood


Feb 25, 2016
Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander


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Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models


Dec 31, 2015
Michael U. Gutmann, Jukka Corander

* In press with the Journal of Machine Learning Research (JMLR). Accepted August 17, 2015 

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Classification and Bayesian Optimization for Likelihood-Free Inference


Feb 19, 2015
Michael U. Gutmann, Jukka Corander, Ritabrata Dutta, Samuel Kaski


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Marginal Pseudo-Likelihood Learning of Markov Network structures


Nov 11, 2014
Johan Pensar, Henrik Nyman, Juha Niiranen, Jukka Corander

* 42 pages 

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Context-specific independence in graphical log-linear models


Sep 09, 2014
Henrik Nyman, Johan Pensar, Timo Koski, Jukka Corander

* 18 pages, 5 figures. arXiv admin note: text overlap with arXiv:1309.6415 

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Marginal and simultaneous predictive classification using stratified graphical models


Jan 31, 2014
Henrik Nyman, Jie Xiong, Johan Pensar, Jukka Corander

* 18 pages, 5 figures 

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Stratified Graphical Models - Context-Specific Independence in Graphical Models


Nov 14, 2013
Henrik Nyman, Johan Pensar, Timo Koski, Jukka Corander

* 19 pages, 7 png figures. In version two the women and mathematics example is replaced with a parliament election data example. Version two contains 22 pages and 8 png figures 

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Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models


Oct 04, 2013
Johan Pensar, Henrik Nyman, Timo Koski, Jukka Corander

* 26 pages, 17 figures 

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Learning Chordal Markov Networks by Constraint Satisfaction


Oct 03, 2013
Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik Nyman, Johan Pensar


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