Jukka Corander

Publication Activity (10 Years)

Years Active: 2004-2023
Publications (10 Years): 66

Top Topics

Importance Sampling

Gaussian Process

Markov Networks

Top Venues

Publications

Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander
Stochastic cluster embedding. Stat. Comput. 33 (1) (2023)
Marko Järvenpää, Jukka Corander
On predictive inference for intractable models via approximate Bayesian computation. Stat. Comput. 33 (2) (2023)
Jukka Corander, Ulpu Remes, Timo Koski
Likelihood-free Model Choice for Simulator-based Models with the Jensen-Shannon Divergence. CoRR (2022)
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) (2022)
Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski
Likelihood-free inference with deep Gaussian processes. Comput. Stat. Data Anal. 174 (2022)
Jukka Corander, Ulpu Remes, Ida Holopainen, Timo Koski
Nonparametric likelihood-free inference with Jensen-Shannon divergence for simulator-based models with categorical output. CoRR (2022)
Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander
Stochastic Cluster Embedding. CoRR (2021)
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) (2021)
Zhirong Yang, Yuwei Chen, Jukka Corander
T-SNE Is Not Optimized to Reveal Clusters in Data. CoRR (2021)
The Tien Mai, Paul Turner, Jukka Corander
Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting. BMC Bioinform. 22 (1) (2021)
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 (2020)
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) (2020)
Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski
Likelihood-Free Inference with Deep Gaussian Processes. CoRR (2020)
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)
Juri Kuronen, Jukka Corander, Johan Pensar
Learning pairwise Markov network structures using correlation neighborhoods. CoRR (2019)
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 (2019)
Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen
A logical approach to context-specific independence. Ann. Pure Appl. Log. 170 (9) (2019)
Yao Lu, Jukka Corander, Zhirong Yang
Doubly Stochastic Neighbor Embedding on Spheres. Pattern Recognit. Lett. 128 (2019)
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 (2018)
Aleksi Sipola, Pekka Marttinen, Jukka Corander
Bacmeta: simulator for genomic evolution in bacterial metapopulations. Bioinform. 34 (13) (2018)
Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander
Likelihood-free inference via classification. Stat. Comput. 28 (2) (2018)
Antti Hyttinen, Johan Pensar, Juha Kontinen, Jukka Corander
Structure Learning for Bayesian Networks over Labeled DAGs. PGM (2018)
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) (2018)
Alberto Pessia, Jukka Corander
Kpax3: Bayesian bi-clustering of large sequence datasets. Bioinform. 34 (12) (2018)
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) (2017)
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) (2017)
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) (2017)
Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta
Inferring Cognitive Models from Data using Approximate Bayesian Computation. CHI (2017)
Luca Martino, Victor Elvira, David Luengo, Jukka Corander
Layered adaptive importance sampling. Stat. Comput. 27 (3) (2017)
Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
Learning Gaussian graphical models with fractional marginal pseudo-likelihood. Int. J. Approx. Reason. 83 (2017)
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 (2017)
Luca Martino, Víctor Elvira, David Luengo, Jukka Corander, Francisco Louzada
Orthogonal parallel MCMC methods for sampling and optimization. Digit. Signal Process. 58 (2016)
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)
Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen
A Logical Approach to Context-Specific Independence. WoLLIC (2016)
Yaqiong Cui, Jukka Sirén, Timo Koski, Jukka Corander
Simultaneous Predictive Gaussian Classifiers. J. Classif. 33 (1) (2016)
Henrik J. Nyman, Jie Xiong, Johan Pensar, Jukka Corander
Marginal and simultaneous predictive classification using stratified graphical models. Adv. Data Anal. Classif. 10 (3) (2016)
Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood. CoRR (2016)
Henrik J. Nyman, Johan Pensar, Timo Koski, Jukka Corander
Context-specific independence in graphical log-linear models. Comput. Stat. 31 (4) (2016)
Michael U. Gutmann, Jukka Corander
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models. J. Mach. Learn. Res. 17 (2016)
Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta
Inverse Modeling of Complex Interactive Behavior with ABC. CoRR (2016)
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) (2016)
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 (2016)
Yao Lu, Zhirong Yang, Jukka Corander
Doubly Stochastic Neighbor Embedding on Spheres. CoRR (2016)
Zhirong Yang, Jukka Corander, Erkki Oja
Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis. J. Mach. Learn. Res. 17 (2016)
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) (2016)
Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela
-penalised sparse precision matrix estimation. CoRR (2016)
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 (2016)
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)
Luca Martino, H. Yang, David Luengo, Juho Kanniainen, Jukka Corander
A fast universal self-tuned sampler within Gibbs sampling. Digit. Signal Process. 47 (2015)
Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Liang Wang, Teemu Roos, Jukka Corander
Fast k-NN search. CoRR (2015)
Mónica F. Bugallo, Luca Martino, Jukka Corander
Adaptive importance sampling in signal processing. Digit. Signal Process. 47 (2015)
Luca Martino, Victor Elvira, David Luengo, Jukka Corander
Layered Adaptive Importance Sampling. CoRR (2015)
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 (2015)
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) (2015)
Luca Martino, Victor Elvira, David Luengo, Jukka Corander
Parallel interacting Markov adaptive importance sampling. EUSIPCO (2015)
Luca Martino, Victor Elvira, David Luengo, Jukka Corander
An Adaptive Population Importance Sampler: Learning From Uncertainty. IEEE Trans. Signal Process. 63 (16) (2015)
Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen
On the volume of a metric ball in unitary group. ISIT (2015)
Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander
On the exact volume of metric balls in complex Grassmann manifolds. ITW Fall (2015)
Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander
Outage Capacity of Rayleigh Product Channels: a Free Probability Approach. CoRR (2015)
Luca Martino, Víctor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander
Smelly parallel MCMC chains. ICASSP (2015)
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) (2015)
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) (2015)
Ruqi Zhang, Zhirong Yang, Jukka Corander
Denoising Cluster Analysis. ICONIP (3) (2015)
Víctor Elvira, Luca Martino, David Luengo, Jukka Corander
A gradient adaptive population importance sampler. ICASSP (2015)
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)
Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander
Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds. CoRR (2015)
Samuel Kaski, Jukka Corander
Preface. AISTATS (2014)
Jukka Kohonen, Jukka Corander
Addition Chains Meet Postage Stamps: Reducing the Number of Multiplications. J. Integer Seq. 17 (3) (2014)
Luca Martino, Victor Elvira, David Luengo, Jukka Corander
An adaptive population importance sampler. ICASSP (2014)
Luca Martino, Victor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander
Orthogonal MCMC algorithms. SSP (2014)
Saikat Chatterjee, David Koslicki, Siyuan Dong, Nicolas Innocenti, Lu Cheng, Yueheng Lan, Mikko Vehkaperä, Mikael Skoglund, Lars K. Rasmussen, Erik Aurell, Jukka Corander
-mer-based estimation of bacterial community composition. Bioinform. 30 (17) (2014)
Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco
Outage capacity of OSTBCs over pico-cellular MIMO channels. ISIT (2014)
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 (2014)
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)
Jukka Corander, Yaqiong Cui, Timo Koski, Jukka Sirén
Have I seen you before? Principles of Bayesian predictive classification revisited. Stat. Comput. 23 (1) (2013)
Johan Pensar, Henrik J. Nyman, Timo Koski, Jukka Corander
Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models. CoRR (2013)
Mikael Sunnåker, Alberto Giovanni Busetto, Elina Numminen, Jukka Corander, Matthieu Foll, Christophe Dessimoz
Approximate Bayesian Computation. PLoS Comput. Biol. 9 (1) (2013)
Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar
Learning Chordal Markov Networks by Constraint Satisfaction. CoRR (2013)
Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar
Learning Chordal Markov Networks by Constraint Satisfaction. NIPS (2013)
Jukka Corander, Timo Koski, Tatjana Pavlenko, Annika Tillander
Bayesian Block-Diagonal Predictive Classifier for Gaussian Data. SMPS (2012)
Jukka Corander, Yaqiong Cui, Timo Koski
Inductive Inference and Partition Exchangeability in Classification. Algorithmic Probability and Friends (2011)
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 (2011)
Pekka Marttinen, Jukka Corander
Efficient Bayesian approach for multilocus association mapping including gene-gene interactions. BMC Bioinform. 11 (2010)
Jukka Corander, Mats Gyllenberg, Timo Koski
Learning Genetic Population Structures Using Minimization of Stochastic Complexity. Entropy 12 (5) (2010)
Pekka Marttinen, Samuel Myllykangas, Jukka Corander
Bayesian clustering and feature selection for cancer tissue samples. BMC Bioinform. 10 (2009)
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)
Pekka Marttinen, Jukka Corander
Bayesian learning of graphical vector autoregressions with unequal lag-lengths. Mach. Learn. 75 (2) (2009)
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) (2009)
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) (2009)
Jukka Corander, Magnus Ekdahl, Timo Koski
Bayesian Unsupervised Learning of DNA Regulatory Binding Regions. Adv. Artif. Intell. 2009 (2009)
Jukka Kohonen, Sarish Talikota, Jukka Corander, Petri Auvinen, Elja Arjas
A Naive Bayes Classifier for Protein Function Prediction. Silico Biol. 9 (1-2) (2009)
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)
Jukka Corander, Magnus Ekdahl, Timo Koski
Parallell interacting MCMC for learning of topologies of graphical models. Data Min. Knowl. Discov. 17 (3) (2008)
Jukka Corander, Jukka Sirén, Elja Arjas
Bayesian spatial modeling of genetic population structure. Comput. Stat. 23 (1) (2008)
Jukka Corander, Pekka Marttinen, Jukka Sirén, Jing Tang
Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinform. 9 (2008)
Pekka Marttinen, Jukka Corander, Petri Törönen, Liisa Holm
Bayesian search of functionally divergent protein subgroups and their function specific residues. Bioinform. 22 (20) (2006)
Jukka Corander, Pekka Marttinen
Bayesian Model Learning Based on Predictive Entropy. J. Log. Lang. Inf. 15 (1-2) (2006)
Jukka Corander, Mats Gyllenberg, Timo Koski
Bayesian model learning based on a parallel MCMC strategy. Stat. Comput. 16 (4) (2006)
Jukka Corander, Patrik Waldmann, Pekka Marttinen, Mikko J. Sillanpää
BAPS 2: enhanced possibilities for the analysis of genetic population structure. Bioinform. 20 (15) (2004)