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ORCIDJukka Corander
Person information
- affiliation: University of Oslo, Norway
- affiliation (former): University of Helsinki, Finnland
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2020 – today
- 2023
[j58]Zhirong Yang
, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic cluster embedding. Stat. Comput. 33(1): 12 (2023)- [j57]Marko Järvenpää, Jukka Corander:
On predictive inference for intractable models via approximate Bayesian computation. Stat. Comput. 33(2): 42 (2023) - 2022
- [j56]Dovydas Kiciatovas, Qingli Guo, Miika Kailas, Henri Pesonen, Jukka Corander, Samuel Kaski, Esa Pitkänen, Ville Mustonen:
Identification of multiplicatively acting modulatory mutational signatures in cancer. BMC Bioinform. 23(1): 522 (2022) - [j55]Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski:
Likelihood-free inference with deep Gaussian processes. Comput. Stat. Data Anal. 174: 107529 (2022) - [i20]Jukka Corander, Ulpu Remes, Ida Holopainen, Timo Koski:
Nonparametric likelihood-free inference with Jensen-Shannon divergence for simulator-based models with categorical output. CoRR abs/2205.10890 (2022) - [i19]Jukka Corander, Ulpu Remes, Timo Koski:
Likelihood-free Model Choice for Simulator-based Models with the Jensen-Shannon Divergence. CoRR abs/2206.04110 (2022) - 2021
- [j54]The Tien Mai, Paul Turner, Jukka Corander:
Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting. BMC Bioinform. 22(1): 164 (2021) - [j53]Kimmo Suotsalo, Yingying Xu, Jukka Corander, Johan Pensar:
High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood. Stat. Comput. 31(6): 73 (2021) - [i18]Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander:
Stochastic Cluster Embedding. CoRR abs/2108.08003 (2021) - [i17]Zhirong Yang, Yuwei Chen, Jukka Corander:
T-SNE Is Not Optimized to Reveal Clusters in Data. CoRR abs/2110.02573 (2021) - 2020
- [j52]Sergio Arredondo-Alonso, Martin Bootsma, Yaïr Hein, Malbert R. C. Rogers, Jukka Corander, Rob J. L. Willems, Anita C. Schürch:
gplas: a comprehensive tool for plasmid analysis using short-read graphs. Bioinform. 36(12): 3874-3876 (2020) - [j51]Johan Pensar, Yingying Xu, Santeri Puranen, Maiju Pesonen, Yoshiyuki Kabashima, Jukka Corander:
High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study. Comput. Stat. Data Anal. 141: 62-76 (2020) - [i16]Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski:
Likelihood-Free Inference with Deep Gaussian Processes. CoRR abs/2006.10571 (2020)
2010 – 2019
- 2019
- [j50]Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen:
A logical approach to context-specific independence. Ann. Pure Appl. Log. 170(9): 975-992 (2019) - [j49]Yao Lu, Jukka Corander, Zhirong Yang:
Doubly Stochastic Neighbor Embedding on Spheres. Pattern Recognit. Lett. 128: 100-106 (2019) - [c21]The Tien Mai, Leiv Rønneberg, Zhi Zhao, Manuela Zucknick, Jukka Corander:
Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure. CIBB 2019: 67-79 - [i15]Johan Pensar, Yingying Xu, Santeri Puranen, Maiju Pesonen, Yoshiyuki Kabashima, Jukka Corander:
High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study. CoRR abs/1901.04345 (2019) - [i14]Juri Kuronen, Jukka Corander, Johan Pensar:
Learning pairwise Markov network structures using correlation neighborhoods. CoRR abs/1910.13832 (2019) - 2018
- [j48]Alberto Pessia, Jukka Corander:
Kpax3: Bayesian bi-clustering of large sequence datasets. Bioinform. 34(12): 2132-2133 (2018) - [j47]Aleksi Sipola, Pekka Marttinen, Jukka Corander:
Bacmeta: simulator for genomic evolution in bacterial metapopulations. Bioinform. 34(13): 2308-2310 (2018) - [j46]John A. Lees, Marco Galardini, Stephen D. Bentley, Jeffrey N. Weiser, Jukka Corander:
pyseer: a comprehensive tool for microbial pangenome-wide association studies. Bioinform. 34(24): 4310-4312 (2018) - [j45]Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski:
ELFI: Engine for Likelihood-Free Inference. J. Mach. Learn. Res. 19: 16:1-16:7 (2018) - [j44]Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander:
Likelihood-free inference via classification. Stat. Comput. 28(2): 411-425 (2018) - [c20]Antti Hyttinen, Johan Pensar, Juha Kontinen, Jukka Corander:
Structure Learning for Bayesian Networks over Labeled DAGs. PGM 2018: 133-144 - 2017
- [j43]Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander:
Learning Gaussian graphical models with fractional marginal pseudo-likelihood. Int. J. Approx. Reason. 83: 21-42 (2017) - [j42]Tomi Janhunen, Martin Gebser, Jussi Rintanen, Henrik J. Nyman, Johan Pensar, Jukka Corander:
Learning discrete decomposable graphical models via constraint optimization. Stat. Comput. 27(1): 115-130 (2017) - [j41]Luca Martino, Victor Elvira, David Luengo, Jukka Corander:
Layered adaptive importance sampling. Stat. Comput. 27(3): 599-623 (2017) - [j40]Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander:
Asymptotic Analysis of Rayleigh Product Channels: A Free Probability Approach. IEEE Trans. Inf. Theory 63(3): 1731-1745 (2017) - [j39]Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen:
From Random Matrix Theory to Coding Theory: Volume of a Metric Ball in Unitary Group. IEEE Trans. Inf. Theory 63(5): 2814-2821 (2017) - [c19]Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta:
Inferring Cognitive Models from Data using Approximate Bayesian Computation. CHI 2017: 1295-1306 - [i13]Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski:
ELFI: Engine for Likelihood Free Inference. CoRR abs/1708.00707 (2017) - 2016
- [j38]Henrik J. Nyman, Jie Xiong, Johan Pensar, Jukka Corander:
Marginal and simultaneous predictive classification using stratified graphical models. Adv. Data Anal. Classif. 10(3): 305-326 (2016) - [j37]Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela:
On the inconsistency of ℓ 1-penalised sparse precision matrix estimation. BMC Bioinform. 17(S-16): 99-107 (2016) - [j36]Yaqiong Cui, Jukka Sirén, Timo Koski, Jukka Corander:
Simultaneous Predictive Gaussian Classifiers. J. Classif. 33(1): 73-102 (2016) - [j35]Teemu Hynninen, Lauri Himanen, V. Parkkinen, T. Musso, Jukka Corander, Adam S. Foster:
An object oriented Python interface for atomistic simulations. Comput. Phys. Commun. 198: 230-237 (2016) - [j34]Henrik J. Nyman, Johan Pensar, Timo Koski, Jukka Corander:
Context-specific independence in graphical log-linear models. Comput. Stat. 31(4): 1493-1512 (2016) - [j33]Luca Martino, Víctor Elvira, David Luengo, Jukka Corander, Francisco Louzada:
Orthogonal parallel MCMC methods for sampling and optimization. Digit. Signal Process. 58: 64-84 (2016) - [j32]Johan Pensar, Henrik J. Nyman, Jarno Lintusaari, Jukka Corander:
The role of local partial independence in learning of Bayesian networks. Int. J. Approx. Reason. 69: 91-105 (2016) - [j31]Michael U. Gutmann, Jukka Corander:
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models. J. Mach. Learn. Res. 17: 125:1-125:47 (2016) - [j30]Zhirong Yang, Jukka Corander, Erkki Oja:
Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis. J. Mach. Learn. Res. 17: 187:1-187:25 (2016) - [j29]Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander:
Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds. IEEE Trans. Inf. Theory 62(9): 5105-5116 (2016) - [c18]Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Elias Jaasaari, Risto Tuomainen, Liang Wang, Jukka Corander, Teemu Roos:
Fast nearest neighbor search through sparse random projections and voting. IEEE BigData 2016: 881-888 - [c17]Lu Wei, Anand D. Sarwate, Jukka Corander, Alfred O. Hero III, Vahid Tarokh:
Analysis of a privacy-preserving PCA algorithm using random matrix theory. GlobalSIP 2016: 1335-1339 - [c16]Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen:
A Logical Approach to Context-Specific Independence. WoLLIC 2016: 165-182 - [p1]Henrik J. Nyman, Johan Pensar, Jukka Corander:
Context-Specific and Local Independence in Markovian Dependence Structures. Dependence Logic 2016: 219-234 - [i12]Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander:
Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood. CoRR abs/1602.07863 (2016) - [i11]Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela:
On the inconsistency of ℓ1-penalised sparse precision matrix estimation. CoRR abs/1603.02532 (2016) - [i10]Yao Lu, Zhirong Yang, Jukka Corander:
Doubly Stochastic Neighbor Embedding on Spheres. CoRR abs/1609.01977 (2016) - [i9]Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta:
Inverse Modeling of Complex Interactive Behavior with ABC. CoRR abs/1612.00653 (2016) - 2015
- [j28]Johan Pensar, Henrik J. Nyman, Timo Koski, Jukka Corander:
Labeled directed acyclic graphs: a generalization of context-specific independence in directed graphical models. Data Min. Knowl. Discov. 29(2): 503-533 (2015) - [j27]Mónica F. Bugallo, Luca Martino, Jukka Corander:
Adaptive importance sampling in signal processing. Digit. Signal Process. 47: 36-49 (2015) - [j26]Luca Martino, H. Yang, David Luengo, Juho Kanniainen, Jukka Corander:
A fast universal self-tuned sampler within Gibbs sampling. Digit. Signal Process. 47: 68-83 (2015) - [j25]Paul Blomstedt, Jing Tang, Jie Xiong, Christian Granlund, Jukka Corander:
A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type. IEEE Trans. Pattern Anal. Mach. Intell. 37(3): 489-498 (2015) - [j24]Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco:
On the Outage Capacity of Orthogonal Space-Time Block Codes Over Multi-Cluster Scattering MIMO Channels. IEEE Trans. Commun. 63(5): 1700-1711 (2015) - [j23]Luca Martino, Victor Elvira, David Luengo, Jukka Corander:
An Adaptive Population Importance Sampler: Learning From Uncertainty. IEEE Trans. Signal Process. 63(16): 4422-4437 (2015) - [c15]Luca Martino, Victor Elvira, David Luengo, Jukka Corander:
Parallel interacting Markov adaptive importance sampling. EUSIPCO 2015: 499-503 - [c14]Luca Martino, Víctor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander:
Smelly parallel MCMC chains. ICASSP 2015: 4070-4074 - [c13]Víctor Elvira, Luca Martino, David Luengo, Jukka Corander:
A gradient adaptive population importance sampler. ICASSP 2015: 4075-4079 - [c12]Ruqi Zhang, Zhirong Yang, Jukka Corander:
Denoising Cluster Analysis. ICONIP (3) 2015: 435-442 - [c11]Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen:
On the volume of a metric ball in unitary group. ISIT 2015: 191-195 - [c10]Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander:
On the finite-SNR Diversity-Multiplexing Tradeoff in large Rayleigh product channels. ISIT 2015: 2593-2597 - [c9]Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander:
On the exact volume of metric balls in complex Grassmann manifolds. ITW Fall 2015: 297-301 - [i8]Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander:
Outage Capacity of Rayleigh Product Channels: a Free Probability Approach. CoRR abs/1502.05516 (2015) - [i7]Luca Martino, Victor Elvira, David Luengo, Jukka Corander:
Layered Adaptive Importance Sampling. CoRR abs/1505.04732 (2015) - [i6]Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen:
From Random Matrix Theory to Coding Theory: Volume of a Metric Ball in Unitary Group. CoRR abs/1506.07259 (2015) - [i5]Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander:
Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds. CoRR abs/1508.00256 (2015) - [i4]Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Liang Wang, Teemu Roos, Jukka Corander:
Fast k-NN search. CoRR abs/1509.06957 (2015) - 2014
- [j22]Saikat Chatterjee, David Koslicki, Siyuan Dong, Nicolas Innocenti, Lu Cheng, Yueheng Lan, Mikko Vehkaperä, Mikael Skoglund, Lars K. Rasmussen, Erik Aurell, Jukka Corander:
SEK: sparsity exploiting k-mer-based estimation of bacterial community composition. Bioinform. 30(17): 2423-2431 (2014) - [j21]Jukka Kohonen, Jukka Corander:
Addition Chains Meet Postage Stamps: Reducing the Number of Multiplications. J. Integer Seq. 17(3): 14.3.4 (2014) - [c8]Samuel Kaski, Jukka Corander:
Preface. AISTATS 2014: i-iv - [c7]Sotiris K. Tasoulis, Lu Cheng, Niko Välimäki, Nicholas J. Croucher, Simon R. Harris, William P. Hanage, Teemu Roos, Jukka Corander:
Random projection based clustering for population genomics. IEEE BigData 2014: 675-682 - [c6]Luca Martino, Victor Elvira, David Luengo, Jukka Corander:
An adaptive population importance sampler. ICASSP 2014: 8038-8042 - [c5]Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco:
Outage capacity of OSTBCs over pico-cellular MIMO channels. ISIT 2014: 616-620 - [c4]Luca Martino, Victor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander:
Orthogonal MCMC algorithms. SSP 2014: 364-367 - [i3]Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco:
On the Outage Capacity of Orthogonal Space-time Block Codes Over Multi-cluster Scattering MIMO Channels. CoRR abs/1403.5571 (2014) - 2013
- [j20]Mikael Sunnåker, Alberto Giovanni Busetto, Elina Numminen, Jukka Corander, Matthieu Foll, Christophe Dessimoz:
Approximate Bayesian Computation. PLoS Comput. Biol. 9(1) (2013) - [j19]Jukka Corander, Yaqiong Cui, Timo Koski, Jukka Sirén:
Have I seen you before? Principles of Bayesian predictive classification revisited. Stat. Comput. 23(1): 59-73 (2013) - [c3]Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar:
Learning Chordal Markov Networks by Constraint Satisfaction. NIPS 2013: 1349-1357 - [i2]Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar:
Learning Chordal Markov Networks by Constraint Satisfaction. CoRR abs/1310.0927 (2013) - [i1]Johan Pensar, Henrik J. Nyman, Timo Koski, Jukka Corander:
Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models. CoRR abs/1310.1187 (2013) - 2012
- [c2]Jukka Corander, Timo Koski, Tatjana Pavlenko, Annika Tillander:
Bayesian Block-Diagonal Predictive Classifier for Gaussian Data. SMPS 2012: 543-551 - 2011
- [j18]Lu Cheng, Thomas R. Connor, David M. Aanensen, Brian G. Spratt, Jukka Corander:
Bayesian semi-supervised classification of bacterial samples using MLST databases. BMC Bioinform. 12: 302 (2011) - [c1]Jukka Corander, Yaqiong Cui, Timo Koski:
Inductive Inference and Partition Exchangeability in Classification. Algorithmic Probability and Friends 2011: 91-105 - 2010
- [j17]Pekka Marttinen, Jukka Corander:
Efficient Bayesian approach for multilocus association mapping including gene-gene interactions. BMC Bioinform. 11: 443 (2010) - [j16]Jukka Corander, Mats Gyllenberg, Timo Koski:
Learning Genetic Population Structures Using Minimization of Stochastic Complexity. Entropy 12(5): 1102-1124 (2010)
2000 – 2009
- 2009
- [j15]Jukka Corander, Mats Gyllenberg, Timo Koski:
Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy. Adv. Data Anal. Classif. 3(1): 3-24 (2009) - [j14]Jukka Corander, Magnus Ekdahl, Timo Koski:
Bayesian Unsupervised Learning of DNA Regulatory Binding Regions. Adv. Artif. Intell. 2009: 219743:1-219743:11 (2009) - [j13]Pekka Marttinen, Samuel Myllykangas, Jukka Corander:
Bayesian clustering and feature selection for cancer tissue samples. BMC Bioinform. 10 (2009) - [j12]Jukka Kohonen, Sarish Talikota, Jukka Corander, Petri Auvinen, Elja Arjas:
A Naive Bayes Classifier for Protein Function Prediction. Silico Biol. 9(1-2): 23-34 (2009) - [j11]Pekka Marttinen, Jukka Corander:
Bayesian learning of graphical vector autoregressions with unequal lag-lengths. Mach. Learn. 75(2): 217-243 (2009) - [j10]Pekka Marttinen, Jing Tang, Bernard De Baets, Peter Dawyndt, Jukka Corander:
Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach. IEEE Trans. Pattern Anal. Mach. Intell. 31(1): 74-85 (2009) - [j9]Jing Tang, William P. Hanage, Christophe Fraser, Jukka Corander:
Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach. PLoS Comput. Biol. 5(8) (2009) - 2008
- [j8]Jukka Corander, Pekka Marttinen, Jukka Sirén, Jing Tang:
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinform. 9 (2008) - [j7]Pekka Marttinen, Adam Baldwin, William P. Hanage, Chris Dowson, Eshwar Mahenthiralingam, Jukka Corander:
Bayesian modeling of recombination events in bacterial populations. BMC Bioinform. 9 (2008) - [j6]Jukka Corander, Jukka Sirén, Elja Arjas:
Bayesian spatial modeling of genetic population structure. Comput. Stat. 23(1): 111-129 (2008) - [j5]Jukka Corander, Magnus Ekdahl, Timo Koski:
Parallell interacting MCMC for learning of topologies of graphical models. Data Min. Knowl. Discov. 17(3): 431-456 (2008) - 2006
- [j4]Pekka Marttinen, Jukka Corander, Petri Törönen, Liisa Holm:
Bayesian search of functionally divergent protein subgroups and their function specific residues. Bioinform. 22(20): 2466-2474 (2006) - [j3]Jukka Corander, Pekka Marttinen:
Bayesian Model Learning Based on Predictive Entropy. J. Log. Lang. Inf. 15(1-2): 5-20 (2006) - [j2]Jukka Corander, Mats Gyllenberg, Timo Koski:
Bayesian model learning based on a parallel MCMC strategy. Stat. Comput. 16(4): 355-362 (2006) - 2004
- [j1]Jukka Corander, Patrik Waldmann, Pekka Marttinen, Mikko J. Sillanpää:
BAPS 2: enhanced possibilities for the analysis of genetic population structure. Bioinform. 20(15): 2363-2369 (2004)
Coauthor Index
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