KTH Mathematics  


Timo Koski

  • Papers 2008-- :

    • T. Koski, Erik Sandstrm, Ulf Sandstrm (2016): Towards field-adjusted production: Estimating research productivity from a zero-truncated distribution. Journal of Informetrics, Vol. 10, 4, Nov. 2016, pp. 1143–1152 Link

    • Yaqiong Cui, Jukka Siren T. Koski, J.Corander (2016): Simultaneous Predictive Gaussian Classifiers. Journal of Classification, First on line Link

    • J. Corander, O. Diekmann och T. Koski, "A tribute to Mats Gyllenberg, on the occasion of his 60th birthday," Journal of Mathematical Biology, vol. 72, no. 4, s. 793-795, 2016.

    • H.Nyman, J. Pensar, H T. Koski, J.Corander (2015): Context-specific independence in graphical log-linear models, in Computational Statistics, July 2015, vol. , pp. 1-20 Link OR get pdf

    • J. Pensar, H. Nyman, T. Koski, J.Corander (2015): Labeled directed acyclical graphs: a generalization of context-specific independence in directed graphical models, in Data Mining and Knowledge Discovery, March 2015, Volume 29, Issue 2, pp 503-533, Link

    • H. Westerlind, K.Imrell, R. Ramanujam, K-M. Myhr, E. E. Gulowsen Celius, H. Harbo, F. Hanne, A. Bang Oturai, A. Hamsten, L. Alfredsson, T. Olsson, I. Kockum, T. Koski, and J. Hillert: Identity-by-descent mapping in a Scandinavian multiple sclerosis cohort. European Journal of Human Genetics, 2014, link

    • H. Nyman, J. Pensar, T. Koski, J.Corander (2014): Stratified Graphical Models - Context-Specific Independence in Graphical Models, in Bayesian Analysis, Vol.9, pp 883-908. Link

    • V. Jskinen, Jie Xiong, J.Corander, and T.Koski (2013): Sparse Markov Chains for Sequence Data. Scandinavian Journal of Statistics,pp (online-preview) . . Link

    • J. Corander, Y. Cui, & T. Koski (2013): Inductive Inference and Partition Exchangeability in Classification. pp. 91-105 in : Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence. Papers from the Ray Solomonoff 85th Memorial Conference. Lecture Notes in Artificial Intelligence, Dowe, David L. (Ed.)l 2013, XV. Link

    • Corander, J. & Koski, T. & Pavlenko, T & Tillander, A. (2013): Bayesian Block-Diagonal Predictive Classifier for Gaussian Data. Synergies of Soft Computing and Statistics for Intelligent Data Analysis Advances in Intelligent Systems and Computing Volume 190, 2013, pp 543-551 Link

    • Koski, T. & Noble, J (2012): A Review of Bayesian Networks and Structure Learning. Mathematica Applicanda (Matematyka Stosowana) Link

    • Corander, J. and Xiong, J. & Cui, Y. and Koski, T. (2012): Optimal Viterbi Bayesian predictive classification for data from finite alphabets. Journal of Statistical Planning and Inference. Link

    • M. Singull & Koski, T. (2012). On the Distribution of Matrix Quadratic Forms. Communications in Statistics - Theory and Methods (CIS). Link

    • J. Corander, Y. Cui, T. Koski & J. Siren(2011): Have I Seen You Before ? Principles of Bayesian Predictive Classification Revisited. Statistics and Computing Link

    • T. Koski, E. Sandstrm, & U. Sandstrm (2011): Estimating Research Productivity from a Zero-Truncated Distribution. PROCEEDINGS OF THE 13TH CONFERENCE OF THE INTERNATIONAL SOCIETY FOR SCIENTOMETRICS AND INFORMETRICS, VOLS 1 AND 2, Pages: 747-755. Link

    • J. Corander, M. Gyllenberg & T.Koski(2011): Learning Genetic Population Structures Using Minimization of Stochastic Complexity. Entropy; Link

    • J. Corander, M.Ekdahl & T.Koski (2009): Bayesian Unsupervised Learning of DNA Regulatory Binding Regions (in Advances in Artificial Intelligence 2009) Link

    • J. Corander, M.Gyllenberg & T.Koski (2009): Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy (in Advances in Data Analysis and Classification 2009) Link

    • J. Corander, M.Ekdahl & T.Koski (2008): Parallell interacting MCMC for learning of graph topologies (in Data Mining and Knowledge Discovery 2008) Link


  • Other writings :


    • Antonin Otahal, Timo Koski, Roman Kotecky and Lucie Fajfrova. (2016): Obituary Martin Janzura. Kybernetika 52 no. 4, 661-664, 2016 Link


    • KTH Roadmap on on Big Data (2014): pdf


    • White Paper on Big Data (2013): pdf


  • Papers (2003-2007) via LiU Research Database:

    • The complete list (two pages) Link


  • Computer science library:


  • Recent selected papers from LiU Research Database:

    • M.Ekdahl & T.Koski (2007): On Concentration of Discrete Distributions with Applications to Supervised Learning of Classifiers Link

    • J. Corander, M. Gyllenberg, & T.Koski (2007): Random Partition Models and Exchangeability for Bayesian Identification of Population StructureLink

    • M.Ekdahl & T.Koski (2006): Bounds for the Loss in Probability of Correct Classification Under Model Based Approximation Link


  • Preprints/technical reports:

    • Timo Koski and Roland Orre (1998): Statistics of the Information Component in Bayesian Neural Networks. pdf

    • Mats Gyllenberg and Timo Koski (2001): Probabilistic Models for Bacterial Taxonomy Link

    • Mats Gyllenberg, Timo Koski and Tatu Lund (2001): BinClass: A Software Package for Classifying Binary Vectors User's Guide pdf

    • Linus Gransson and Timo Koski (2002): Using a Dynamic Bayesian Network to Learn Genetic Interactions. pdf

    • Mats Gyllenberg, Jonas Carlsson and Timo Koski (2002): Bayesian Network Classification of Binarized DNA Fingerprint Patterns. ps

    • Harry Hurd and Timo Koski (2002): The Wold isomorphism for cyclostationary sequences. pdf



  • A news item from 'Microbiology` :




    Senast uppdaterad 2014-05-05.