BAPS 2: enhanced possibilities for the analysis of genetic population structure. - Jukka Corander; Patrik Waldmann; Pekka Marttinen; Mikko J. Sillanpää (Bioinform., 2004)

Bayesian search of functionally divergent protein subgroups and their function specific residues. - Pekka Marttinen; Jukka Corander; Petri Törönen; Liisa Holm (Bioinform., 2006)

Bayesian Model Learning Based on Predictive Entropy. - Jukka Corander; Pekka Marttinen (J. Log. Lang. Inf., 2006)

Bayesian model learning based on a parallel MCMC strategy. - Jukka Corander; Mats Gyllenberg; Timo Koski (Stat. Comput., 2006)

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. - Jukka Corander; Pekka Marttinen; Jukka Sirén; Jing Tang 002 (BMC Bioinform., 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)

Bayesian spatial modeling of genetic population structure. - Jukka Corander; Jukka Sirén; Elja Arjas (Comput. Stat., 2008)

Parallell interacting MCMC for learning of topologies of graphical models. - Jukka Corander; Magnus Ekdahl; Timo Koski (Data Min. Knowl. Discov., 2008)

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)

Bayesian Unsupervised Learning of DNA Regulatory Binding Regions. - Jukka Corander; Magnus Ekdahl; Timo Koski (Adv. Artif. Intell., 2009)

Bayesian clustering and feature selection for cancer tissue samples. - Pekka Marttinen; Samuel Myllykangas; Jukka Corander (BMC Bioinform., 2009)

A Naive Bayes Classifier for Protein Function Prediction. - Jukka Kohonen; Sarish Talikota; Jukka Corander; Petri Auvinen; Elja Arjas (Silico Biol., 2009)

Bayesian learning of graphical vector autoregressions with unequal lag-lengths. - Pekka Marttinen; Jukka Corander (Mach. Learn., 2009)

Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach. - Pekka Marttinen; Jing Tang 002; Bernard De Baets; Peter Dawyndt; Jukka Corander (IEEE Trans. Pattern Anal. Mach. Intell., 2009)

Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach. - Jing Tang 002; William P. Hanage; Christophe Fraser; Jukka Corander (PLoS Comput. Biol., 2009)

Efficient Bayesian approach for multilocus association mapping including gene-gene interactions. - Pekka Marttinen; Jukka Corander (BMC Bioinform., 2010)

Learning Genetic Population Structures Using Minimization of Stochastic Complexity. - Jukka Corander; Mats Gyllenberg; Timo Koski (Entropy, 2010)

Inductive Inference and Partition Exchangeability in Classification. - Jukka Corander; Yaqiong Cui; Timo Koski (Algorithmic Probability and Friends, 2011)

Bayesian semi-supervised classification of bacterial samples using MLST databases. - Lu Cheng 004; Thomas R. Connor; David M. Aanensen; Brian G. Spratt; Jukka Corander (BMC Bioinform., 2011)

Bayesian Block-Diagonal Predictive Classifier for Gaussian Data. - Jukka Corander; Timo Koski; Tatjana Pavlenko; Annika Tillander (SMPS, 2012)

Learning Chordal Markov Networks by Constraint Satisfaction. - Jukka Corander; Tomi Janhunen; Jussi Rintanen; Henrik J. Nyman; Johan Pensar (NIPS, 2013)

Approximate Bayesian Computation. - Mikael Sunnåker; Alberto Giovanni Busetto; Elina Numminen; Jukka Corander; Matthieu Foll; Christophe Dessimoz (PLoS Comput. Biol., 2013)

Have I seen you before? Principles of Bayesian predictive classification revisited. - Jukka Corander; Yaqiong Cui; Timo Koski; Jukka Sirén (Stat. Comput., 2013)

Preface. - Samuel Kaski; Jukka Corander (AISTATS, 2014)

Random projection based clustering for population genomics. - Sotiris K. Tasoulis; Lu Cheng 004; Niko Välimäki; Nicholas J. Croucher; Simon R. Harris; William P. Hanage; Teemu Roos; Jukka Corander (IEEE BigData, 2014)

An adaptive population importance sampler. - Luca Martino; Victor Elvira; David Luengo; Jukka Corander (ICASSP, 2014)

Outage capacity of OSTBCs over pico-cellular MIMO channels. - Lu Wei 001; Zhong Zheng 001; Jukka Corander; Giorgio Taricco (ISIT, 2014)

Orthogonal MCMC algorithms. - Luca Martino; Victor Elvira; David Luengo; Antonio Artés-Rodríguez; Jukka Corander (SSP, 2014)

SEK: sparsity exploiting k-mer-based estimation of bacterial community composition. - Saikat Chatterjee; David Koslicki; Siyuan Dong; Nicolas Innocenti; Lu Cheng 004; Yueheng Lan; Mikko Vehkaperä; Mikael Skoglund; Lars K. Rasmussen; Erik Aurell; Jukka Corander (Bioinform., 2014)

Addition Chains Meet Postage Stamps: Reducing the Number of Multiplications. - Jukka Kohonen; Jukka Corander (J. Integer Seq., 2014)

Parallel interacting Markov adaptive importance sampling. - Luca Martino; Victor Elvira; David Luengo; Jukka Corander (EUSIPCO, 2015)

A gradient adaptive population importance sampler. - Víctor Elvira; Luca Martino; David Luengo; Jukka Corander (ICASSP, 2015)

Smelly parallel MCMC chains. - Luca Martino; Víctor Elvira; David Luengo; Antonio Artés-Rodríguez; Jukka Corander (ICASSP, 2015)

Denoising Cluster Analysis. - Ruqi Zhang; Zhirong Yang; Jukka Corander (ICONIP (3), 2015)

On the volume of a metric ball in unitary group. - Lu Wei 001; Renaud-Alexandre Pitaval; Jukka Corander; Olav Tirkkonen (ISIT, 2015)

On the finite-SNR Diversity-Multiplexing Tradeoff in large Rayleigh product channels. - Zhong Zheng 001; Lu Wei 001; Roland Speicher; Ralf R. Müller; Jyri Hämäläinen; Jukka Corander (ISIT, 2015)

On the exact volume of metric balls in complex Grassmann manifolds. - Renaud-Alexandre Pitaval; Lu Wei 001; Olav Tirkkonen; Jukka Corander (ITW Fall, 2015)

Fast k-NN search. - Ville Hyvönen; Teemu Pitkänen; Sotiris K. Tasoulis; Liang Wang 009; Teemu Roos; Jukka Corander (CoRR, 2015)

Outage Capacity of Rayleigh Product Channels: a Free Probability Approach. - Zhong Zheng 001; Lu Wei 001; Roland Speicher; Ralf R. Müller; Jyri Hämäläinen; Jukka Corander (CoRR, 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)

Adaptive importance sampling in signal processing. - Mónica F. Bugallo; Luca Martino; Jukka Corander (Digit. Signal Process., 2015)

A fast universal self-tuned sampler within Gibbs sampling. - Luca Martino; H. Yang; David Luengo; Juho Kanniainen; Jukka Corander (Digit. Signal Process., 2015)

A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type. - Paul Blomstedt; Jing Tang 002; Jie Xiong; Christian Granlund; Jukka Corander (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

On the Outage Capacity of Orthogonal Space-Time Block Codes Over Multi-Cluster Scattering MIMO Channels. - Lu Wei 001; Zhong Zheng 001; Jukka Corander; Giorgio Taricco (IEEE Trans. Commun., 2015)

An Adaptive Population Importance Sampler: Learning From Uncertainty. - Luca Martino; Victor Elvira; David Luengo; Jukka Corander (IEEE Trans. Signal Process., 2015)

Context-Specific and Local Independence in Markovian Dependence Structures. - Henrik J. Nyman; Johan Pensar; Jukka Corander (Dependence Logic, 2016)

Fast nearest neighbor search through sparse random projections and voting. - Ville Hyvönen; Teemu Pitkänen; Sotiris K. Tasoulis; Elias Jaasaari; Risto Tuomainen; Liang Wang 009; Jukka Corander; Teemu Roos (IEEE BigData, 2016)

Analysis of a privacy-preserving PCA algorithm using random matrix theory. - Lu Wei 001; Anand D. Sarwate; Jukka Corander; Alfred O. Hero III; Vahid Tarokh (GlobalSIP, 2016)

Marginal and simultaneous predictive classification using stratified graphical models. - Henrik J. Nyman; Jie Xiong; Johan Pensar; Jukka Corander (Adv. Data Anal. 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)

Simultaneous Predictive Gaussian Classifiers. - Yaqiong Cui; Jukka Sirén; Timo Koski; Jukka Corander (J. Classif., 2016)

On the inconsistency of ℓ1-penalised sparse precision matrix estimation. - Otte Heinävaara; Janne Leppä-aho; Jukka Corander; Antti Honkela (CoRR, 2016)

Inverse Modeling of Complex Interactive Behavior with ABC. - Antti Kangasrääsiö; Kumaripaba Athukorala; Andrew Howes 001; Jukka Corander; Samuel Kaski; Antti Oulasvirta (CoRR, 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)

Context-specific independence in graphical log-linear models. - Henrik J. Nyman; Johan Pensar; Timo Koski; Jukka Corander (Comput. Stat., 2016)

Orthogonal parallel MCMC methods for sampling and optimization. - Luca Martino; Víctor Elvira; David Luengo; Jukka Corander; Francisco Louzada 001 (Digit. Signal Process., 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)

Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models. - Michael U. Gutmann; Jukka Corander (J. Mach. Learn. Res., 2016)

Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis. - Zhirong Yang; Jukka Corander; Erkki Oja (J. Mach. Learn. Res., 2016)

Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds. - Renaud-Alexandre Pitaval; Lu Wei 001; Olav Tirkkonen; Jukka Corander (IEEE Trans. Inf. Theory, 2016)

Inferring Cognitive Models from Data using Approximate Bayesian Computation. - Antti Kangasrääsiö; Kumaripaba Athukorala; Andrew Howes 001; Jukka Corander; Samuel Kaski; Antti Oulasvirta (CHI, 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)

Learning Gaussian graphical models with fractional marginal pseudo-likelihood. - Janne Leppä-aho; Johan Pensar; Teemu Roos; Jukka Corander (Int. J. Approx. Reason., 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)

Layered adaptive importance sampling. - Luca Martino; Victor Elvira; David Luengo; Jukka Corander (Stat. Comput., 2017)

From Random Matrix Theory to Coding Theory: Volume of a Metric Ball in Unitary Group. - Lu Wei 001; Renaud-Alexandre Pitaval; Jukka Corander; Olav Tirkkonen (IEEE Trans. Inf. Theory, 2017)

Asymptotic Analysis of Rayleigh Product Channels: A Free Probability Approach. - Zhong Zheng 001; Lu Wei 001; Roland Speicher; Ralf R. Müller; Jyri Hämäläinen; Jukka Corander (IEEE Trans. Inf. Theory, 2017)

Structure Learning for Bayesian Networks over Labeled DAGs. - Antti Hyttinen; Johan Pensar; Juha Kontinen; Jukka Corander (PGM, 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)

Kpax3: Bayesian bi-clustering of large sequence datasets. - Alberto Pessia; Jukka Corander (Bioinform., 2018)

Bacmeta: simulator for genomic evolution in bacterial metapopulations. - Aleksi Sipola; Pekka Marttinen; Jukka Corander (Bioinform., 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)

Likelihood-free inference via classification. - Michael U. Gutmann; Ritabrata Dutta; Samuel Kaski; Jukka Corander (Stat. Comput., 2018)

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 (CIBB, 2019)

A logical approach to context-specific independence. - Jukka Corander; Antti Hyttinen; Juha Kontinen; Johan Pensar; Jouko Väänänen (Ann. Pure Appl. Log., 2019)

Learning pairwise Markov network structures using correlation neighborhoods. - Juri Kuronen; Jukka Corander; Johan Pensar (CoRR, 2019)

Doubly Stochastic Neighbor Embedding on Spheres. - Yao Lu; Jukka Corander; Zhirong Yang (Pattern Recognit. Lett., 2019)

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)

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)

Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting. - The Tien Mai; Paul Turner; Jukka Corander (BMC Bioinform., 2021)

T-SNE Is Not Optimized to Reveal Clusters in Data. - Zhirong Yang; Yuwei Chen; Jukka Corander (CoRR, 2021)

On the Jensen-Shannon divergence and the variation distance for categorical probability distributions. - Jukka Corander; Ulpu Remes; Timo Koski (Kybernetika, 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)

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)

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)

Likelihood-free Model Choice for Simulator-based Models with the Jensen-Shannon Divergence. - Jukka Corander; Ulpu Remes; Timo Koski (CoRR, 2022)

Likelihood-free inference with deep Gaussian processes. - Alexander Aushev; Henri Pesonen; Markus Heinonen; Jukka Corander; Samuel Kaski (Comput. Stat. Data Anal., 2022)

Stochastic cluster embedding. - Zhirong Yang; Yuwei Chen; Denis Sedov; Samuel Kaski; Jukka Corander (Stat. Comput., 2023)

On predictive inference for intractable models via approximate Bayesian computation. - Marko Järvenpää; Jukka Corander (Stat. Comput., 2023)

Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation. - Henri Pesonen; Jukka Corander (Comput. Stat. Data Anal., 2025)