Jukka Corander

According to our database, Jukka Corander authored at least 90 papers between 2004 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2025

Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation.

Henri Pesonen, Jukka Corander

Comput. Stat. Data Anal., 2025

2023

On predictive inference for intractable models via approximate Bayesian computation.

Marko Järvenpää, Jukka Corander

Stat. Comput., April, 2023

Stochastic cluster embedding.

Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander

Stat. Comput., 2023

2022

Likelihood-free inference with deep Gaussian processes.

Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski

Comput. Stat. Data Anal., 2022

Likelihood-free Model Choice for Simulator-based Models with the Jensen-Shannon Divergence.

Jukka Corander, Ulpu Remes, Timo Koski

CoRR, 2022

Nonparametric likelihood-free inference with Jensen-Shannon divergence for simulator-based models with categorical output.

Jukka Corander, Ulpu Remes, Ida Holopainen, Timo Koski

CoRR, 2022

Identification of multiplicatively acting modulatory mutational signatures in cancer.

Dovydas Kiciatovas, Qingli Guo, Miika Kailas, Henri Pesonen, Jukka Corander, Samuel Kaski, Esa Pitkänen, Ville Mustonen

BMC Bioinform., 2022

2021

High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood.

Kimmo Suotsalo, Yingying Xu, Jukka Corander, Johan Pensar

Stat. Comput., 2021

On the Jensen-Shannon divergence and the variation distance for categorical probability distributions.

Jukka Corander, Ulpu Remes, Timo Koski

Kybernetika, 2021

T-SNE Is Not Optimized to Reveal Clusters in Data.

Zhirong Yang, Yuwei Chen, Jukka Corander

CoRR, 2021

Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting.

The Tien Mai, Paul Turner, Jukka Corander

BMC Bioinform., 2021

2020

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

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

Comput. Stat. Data Anal., 2020

gplas: a comprehensive tool for plasmid analysis using short-read graphs.

Sergio Arredondo-Alonso, Martin Bootsma, Yaïr Hein, Malbert R. C. Rogers, Jukka Corander, Rob J. L. Willems, Anita C. Schürch

Bioinform., 2020

2019

Doubly Stochastic Neighbor Embedding on Spheres.

Yao Lu, Jukka Corander, Zhirong Yang

Pattern Recognit. Lett., 2019

Learning pairwise Markov network structures using correlation neighborhoods.

Juri Kuronen, Jukka Corander, Johan Pensar

CoRR, 2019

Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure.

The Tien Mai, Leiv Rønneberg, Zhi Zhao, Manuela Zucknick, Jukka Corander

Proceedings of the Computational Intelligence Methods for Bioinformatics and Biostatistics, 2019

2018

Likelihood-free inference via classification.

Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander

Stat. Comput., 2018

ELFI: Engine for Likelihood-Free Inference.

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

J. Mach. Learn. Res., 2018

Bacmeta: simulator for genomic evolution in bacterial metapopulations.

Aleksi Sipola, Pekka Marttinen, Jukka Corander

Bioinform., 2018

Kpax3: Bayesian bi-clustering of large sequence datasets.

Alberto Pessia, Jukka Corander

Bioinform., 2018

pyseer: a comprehensive tool for microbial pangenome-wide association studies.

John A. Lees, Marco Galardini, Stephen D. Bentley, Jeffrey N. Weiser, Jukka Corander

Bioinform., 2018

Structure Learning for Bayesian Networks over Labeled DAGs.

Antti Hyttinen, Johan Pensar, Juha Kontinen, Jukka Corander

Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017

Asymptotic Analysis of Rayleigh Product Channels: A Free Probability Approach.

Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander

IEEE Trans. Inf. Theory, 2017

From Random Matrix Theory to Coding Theory: Volume of a Metric Ball in Unitary Group.

Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen

IEEE Trans. Inf. Theory, 2017

Layered adaptive importance sampling.

Luca Martino, Victor Elvira, David Luengo, Jukka Corander

Stat. Comput., 2017

Learning discrete decomposable graphical models via constraint optimization.

Tomi Janhunen, Martin Gebser, Jussi Rintanen, Henrik J. Nyman, Johan Pensar, Jukka Corander

Stat. Comput., 2017

Learning Gaussian graphical models with fractional marginal pseudo-likelihood.

Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander

Int. J. Approx. Reason., 2017

ELFI: Engine for Likelihood Free Inference.

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

CoRR, 2017

Inferring Cognitive Models from Data using Approximate Bayesian Computation.

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

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017

2016

Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds.

Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander

IEEE Trans. Inf. Theory, 2016

Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis.

Zhirong Yang, Jukka Corander, Erkki Oja

J. Mach. Learn. Res., 2016

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

Michael U. Gutmann, Jukka Corander

J. Mach. Learn. Res., 2016

The role of local partial independence in learning of Bayesian networks.

Johan Pensar, Henrik J. Nyman, Jarno Lintusaari, Jukka Corander

Int. J. Approx. Reason., 2016

Orthogonal parallel MCMC methods for sampling and optimization.

Luca Martino, Víctor Elvira, David Luengo, Jukka Corander, Francisco Louzada

Digit. Signal Process., 2016

Context-specific independence in graphical log-linear models.

Henrik J. Nyman, Johan Pensar, Timo Koski, Jukka Corander

Comput. Stat., 2016

An object oriented Python interface for atomistic simulations.

Teemu Hynninen, Lauri Himanen, V. Parkkinen, T. Musso, Jukka Corander, Adam S. Foster

Comput. Phys. Commun., 2016

Inverse Modeling of Complex Interactive Behavior with ABC.

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

CoRR, 2016

On the inconsistency of ℓ₁-penalised sparse precision matrix estimation.

Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela

CoRR, 2016

Simultaneous Predictive Gaussian Classifiers.

Yaqiong Cui, Jukka Sirén, Timo Koski, Jukka Corander

J. Classif., 2016

On the inconsistency of ℓ 1-penalised sparse precision matrix estimation.

Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela

BMC Bioinform., 2016

Marginal and simultaneous predictive classification using stratified graphical models.

Henrik J. Nyman, Jie Xiong, Johan Pensar, Jukka Corander

Adv. Data Anal. Classif., 2016

A Logical Approach to Context-Specific Independence.

Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen

Proceedings of the Logic, Language, Information, and Computation, 2016

Analysis of a privacy-preserving PCA algorithm using random matrix theory.

Lu Wei, Anand D. Sarwate, Jukka Corander, Alfred O. Hero III, Vahid Tarokh

Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Fast nearest neighbor search through sparse random projections and voting.

Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Elias Jaasaari, Risto Tuomainen, Liang Wang, Jukka Corander, Teemu Roos

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

Context-Specific and Local Independence in Markovian Dependence Structures.

Henrik J. Nyman, Johan Pensar, Jukka Corander

Proceedings of the Dependence Logic, Theory and Applications, 2016

2015

An Adaptive Population Importance Sampler: Learning From Uncertainty.

Luca Martino, Victor Elvira, David Luengo, Jukka Corander

IEEE Trans. Signal Process., 2015

On the Outage Capacity of Orthogonal Space-Time Block Codes Over Multi-Cluster Scattering MIMO Channels.

Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco

IEEE Trans. Commun., 2015

A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type.

Paul Blomstedt, Jing Tang, Jie Xiong, Christian Granlund, Jukka Corander

IEEE Trans. Pattern Anal. Mach. Intell., 2015

A fast universal self-tuned sampler within Gibbs sampling.

Luca Martino, H. Yang, David Luengo, Juho Kanniainen, Jukka Corander

Digit. Signal Process., 2015

Adaptive importance sampling in signal processing.

Mónica F. Bugallo, Luca Martino, Jukka Corander

Digit. Signal Process., 2015

Labeled directed acyclic graphs: a generalization of context-specific independence in directed graphical models.

Johan Pensar, Henrik J. Nyman, Timo Koski, Jukka Corander

Data Min. Knowl. Discov., 2015

Outage Capacity of Rayleigh Product Channels: a Free Probability Approach.

Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander

CoRR, 2015

Fast k-NN search.

Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Liang Wang, Teemu Roos, Jukka Corander

CoRR, 2015

On the exact volume of metric balls in complex Grassmann manifolds.

Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander

Proceedings of the 2015 IEEE Information Theory Workshop, 2015

On the finite-SNR Diversity-Multiplexing Tradeoff in large Rayleigh product channels.

Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander

Proceedings of the IEEE International Symposium on Information Theory, 2015

On the volume of a metric ball in unitary group.

Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen

Proceedings of the IEEE International Symposium on Information Theory, 2015

Denoising Cluster Analysis.

Ruqi Zhang, Zhirong Yang, Jukka Corander

Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Smelly parallel MCMC chains.

Luca Martino, Víctor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

A gradient adaptive population importance sampler.

Víctor Elvira, Luca Martino, David Luengo, Jukka Corander

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Parallel interacting Markov adaptive importance sampling.

Luca Martino, Victor Elvira, David Luengo, Jukka Corander

Proceedings of the 23rd European Signal Processing Conference, 2015

2014

Addition Chains Meet Postage Stamps: Reducing the Number of Multiplications.

Jukka Kohonen, Jukka Corander

J. Integer Seq., 2014

SEK: sparsity exploiting <i>k</i>-mer-based estimation of bacterial community composition.

Saikat Chatterjee, David Koslicki, Siyuan Dong, Nicolas Innocenti, Lu Cheng, Yueheng Lan, Mikko Vehkaperä, Mikael Skoglund, Lars K. Rasmussen, Erik Aurell, Jukka Corander

Bioinform., 2014

Orthogonal MCMC algorithms.

Luca Martino, Victor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander

Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Outage capacity of OSTBCs over pico-cellular MIMO channels.

Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco

Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

An adaptive population importance sampler.

Luca Martino, Victor Elvira, David Luengo, Jukka Corander

Proceedings of the IEEE International Conference on Acoustics, 2014

Random projection based clustering for population genomics.

Sotiris K. Tasoulis, Lu Cheng, Niko Välimäki, Nicholas J. Croucher, Simon R. Harris, William P. Hanage, Teemu Roos, Jukka Corander

Proceedings of the 2014 IEEE International Conference on Big Data (IEEE BigData 2014), 2014

Preface.

Samuel Kaski, Jukka Corander

Proceedings of the Seventeenth International Conference on Artificial Intelligence and Statistics, 2014

2013

Have I seen you before? Principles of Bayesian predictive classification revisited.

Jukka Corander, Yaqiong Cui, Timo Koski, Jukka Sirén

Stat. Comput., 2013

Approximate Bayesian Computation.

Mikael Sunnåker, Alberto Giovanni Busetto, Elina Numminen, Jukka Corander, Matthieu Foll, Christophe Dessimoz

PLoS Comput. Biol., 2013

Learning Chordal Markov Networks by Constraint Satisfaction.

Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

2012

Bayesian Block-Diagonal Predictive Classifier for Gaussian Data.

Jukka Corander, Timo Koski, Tatjana Pavlenko, Annika Tillander

Proceedings of the Synergies of Soft Computing and Statistics for Intelligent Data Analysis, 2012

2011

Bayesian semi-supervised classification of bacterial samples using MLST databases.

Lu Cheng, Thomas R. Connor, David M. Aanensen, Brian G. Spratt, Jukka Corander

BMC Bioinform., 2011

Inductive Inference and Partition Exchangeability in Classification.

Jukka Corander, Yaqiong Cui, Timo Koski

Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011

2010

Learning Genetic Population Structures Using Minimization of Stochastic Complexity.

Jukka Corander, Mats Gyllenberg, Timo Koski

Entropy, 2010

Efficient Bayesian approach for multilocus association mapping including gene-gene interactions.

Pekka Marttinen, Jukka Corander

BMC Bioinform., 2010

2009

Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach.

Jing Tang, William P. Hanage, Christophe Fraser, Jukka Corander

PLoS Comput. Biol., 2009

Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach.

Pekka Marttinen, Jing Tang, Bernard De Baets, Peter Dawyndt, Jukka Corander

IEEE Trans. Pattern Anal. Mach. Intell., 2009

Bayesian learning of graphical vector autoregressions with unequal lag-lengths.

Pekka Marttinen, Jukka Corander

Mach. Learn., 2009

A Naive Bayes Classifier for Protein Function Prediction.

Jukka Kohonen, Sarish Talikota, Jukka Corander, Petri Auvinen, Elja Arjas

Silico Biol., 2009

Bayesian clustering and feature selection for cancer tissue samples.

Pekka Marttinen, Samuel Myllykangas, Jukka Corander

BMC Bioinform., 2009

Bayesian Unsupervised Learning of DNA Regulatory Binding Regions.

Jukka Corander, Magnus Ekdahl, Timo Koski

Adv. Artif. Intell., 2009

Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy.

Jukka Corander, Mats Gyllenberg, Timo Koski

Adv. Data Anal. Classif., 2009

2008

Parallell interacting MCMC for learning of topologies of graphical models.

Jukka Corander, Magnus Ekdahl, Timo Koski

Data Min. Knowl. Discov., 2008

Bayesian spatial modeling of genetic population structure.

Jukka Corander, Jukka Sirén, Elja Arjas

Comput. Stat., 2008

Bayesian modeling of recombination events in bacterial populations.

Pekka Marttinen, Adam Baldwin, William P. Hanage, Chris Dowson, Eshwar Mahenthiralingam, Jukka Corander

BMC Bioinform., 2008

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations.

Jukka Corander, Pekka Marttinen, Jukka Sirén, Jing Tang

BMC Bioinform., 2008

2006

Bayesian model learning based on a parallel MCMC strategy.

Jukka Corander, Mats Gyllenberg, Timo Koski

Stat. Comput., 2006

Bayesian Model Learning Based on Predictive Entropy.

Jukka Corander, Pekka Marttinen

J. Log. Lang. Inf., 2006

Bayesian search of functionally divergent protein subgroups and their function specific residues.

Pekka Marttinen, Jukka Corander, Petri Törönen, Liisa Holm

Bioinform., 2006

2004

BAPS 2: enhanced possibilities for the analysis of genetic population structure.

Jukka Corander, Patrik Waldmann, Pekka Marttinen, Mikko J. Sillanpää

Bioinform., 2004