Jukka Corander

According to our database1, Jukka Corander authored at least 79 papers between 2004 and 2020.

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Bibliography

2020
High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study.
Comput. Stat. Data Anal., 2020

Likelihood-Free Inference with Deep Gaussian Processes.
CoRR, 2020

gplas: a comprehensive tool for plasmid analysis using short-read graphs.
Bioinform., 2020

2019
Doubly Stochastic Neighbor Embedding on Spheres.
Pattern Recognit. Lett., 2019

Learning pairwise Markov network structures using correlation neighborhoods.
CoRR, 2019

A logical approach to context-specific independence.
Ann. Pure Appl. Log., 2019

2018
Likelihood-free inference via classification.
Stat. Comput., 2018

ELFI: Engine for Likelihood-Free Inference.
J. Mach. Learn. Res., 2018

Bacmeta: simulator for genomic evolution in bacterial metapopulations.
Bioinform., 2018

Kpax3: Bayesian bi-clustering of large sequence datasets.
Bioinform., 2018

pyseer: a comprehensive tool for microbial pangenome-wide association studies.
Bioinform., 2018

Structure Learning for Bayesian Networks over Labeled DAGs.
Proceedings of the International Conference on Probabilistic Graphical Models, 2018

2017
Asymptotic Analysis of Rayleigh Product Channels: A Free Probability Approach.
IEEE Trans. Inf. Theory, 2017

From Random Matrix Theory to Coding Theory: Volume of a Metric Ball in Unitary Group.
IEEE Trans. Inf. Theory, 2017

Layered adaptive importance sampling.
Stat. Comput., 2017

Learning discrete decomposable graphical models via constraint optimization.
Stat. Comput., 2017

Learning Gaussian graphical models with fractional marginal pseudo-likelihood.
Int. J. Approx. Reason., 2017

ELFI: Engine for Likelihood Free Inference.
CoRR, 2017

Inferring Cognitive Models from Data using Approximate Bayesian Computation.
Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017

2016
Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds.
IEEE Trans. Inf. Theory, 2016

Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis.
J. Mach. Learn. Res., 2016

Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models.
J. Mach. Learn. Res., 2016

The role of local partial independence in learning of Bayesian networks.
Int. J. Approx. Reason., 2016

Orthogonal parallel MCMC methods for sampling and optimization.
Digit. Signal Process., 2016

Context-specific independence in graphical log-linear models.
Comput. Stat., 2016

An object oriented Python interface for atomistic simulations.
Comput. Phys. Commun., 2016

Inverse Modeling of Complex Interactive Behavior with ABC.
CoRR, 2016

On the inconsistency of ℓ<sub>1</sub>-penalised sparse precision matrix estimation.
CoRR, 2016

Simultaneous Predictive Gaussian Classifiers.
J. Classif., 2016

On the inconsistency of ℓ 1-penalised sparse precision matrix estimation.
BMC Bioinform., 2016

Marginal and simultaneous predictive classification using stratified graphical models.
Adv. Data Anal. Classif., 2016

Analysis of a privacy-preserving PCA algorithm using random matrix theory.
Proceedings of the 2016 IEEE Global Conference on Signal and Information Processing, 2016

Fast nearest neighbor search through sparse random projections and voting.
Proceedings of the 2016 IEEE International Conference on Big Data, 2016

Context-Specific and Local Independence in Markovian Dependence Structures.
Proceedings of the Dependence Logic, Theory and Applications, 2016

2015
An Adaptive Population Importance Sampler: Learning From Uncertainty.
IEEE Trans. Signal Process., 2015

On the Outage Capacity of Orthogonal Space-Time Block Codes Over Multi-Cluster Scattering MIMO Channels.
IEEE Trans. Commun., 2015

A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type.
IEEE Trans. Pattern Anal. Mach. Intell., 2015

A fast universal self-tuned sampler within Gibbs sampling.
Digit. Signal Process., 2015

Adaptive importance sampling in signal processing.
Digit. Signal Process., 2015

Labeled directed acyclic graphs: a generalization of context-specific independence in directed graphical models.
Data Min. Knowl. Discov., 2015

Outage Capacity of Rayleigh Product Channels: a Free Probability Approach.
CoRR, 2015

Fast k-NN search.
CoRR, 2015

On the exact volume of metric balls in complex Grassmann manifolds.
Proceedings of the 2015 IEEE Information Theory Workshop, 2015

On the finite-SNR Diversity-Multiplexing Tradeoff in large Rayleigh product channels.
Proceedings of the IEEE International Symposium on Information Theory, 2015

On the volume of a metric ball in unitary group.
Proceedings of the IEEE International Symposium on Information Theory, 2015

Denoising Cluster Analysis.
Proceedings of the Neural Information Processing - 22nd International Conference, 2015

Smelly parallel MCMC chains.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

A gradient adaptive population importance sampler.
Proceedings of the 2015 IEEE International Conference on Acoustics, 2015

Parallel interacting Markov adaptive importance sampling.
Proceedings of the 23rd European Signal Processing Conference, 2015

2014
Addition Chains Meet Postage Stamps: Reducing the Number of Multiplications.
J. Integer Seq., 2014

SEK: sparsity exploiting <i>k</i>-mer-based estimation of bacterial community composition.
Bioinform., 2014

Orthogonal MCMC algorithms.
Proceedings of the IEEE Workshop on Statistical Signal Processing, 2014

Outage capacity of OSTBCs over pico-cellular MIMO channels.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

An adaptive population importance sampler.
Proceedings of the IEEE International Conference on Acoustics, 2014

Random projection based clustering for population genomics.
Proceedings of the 2014 IEEE International Conference on Big Data, 2014

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

2013
Have I seen you before? Principles of Bayesian predictive classification revisited.
Stat. Comput., 2013

Approximate Bayesian Computation.
PLoS Comput. Biol., 2013

Learning Chordal Markov Networks by Constraint Satisfaction.
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.
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.
BMC Bioinform., 2011

Inductive Inference and Partition Exchangeability in Classification.
Proceedings of the Algorithmic Probability and Friends. Bayesian Prediction and Artificial Intelligence, 2011

2010
Learning Genetic Population Structures Using Minimization of Stochastic Complexity.
Entropy, 2010

Efficient Bayesian approach for multilocus association mapping including gene-gene interactions.
BMC Bioinform., 2010

2009
Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach.
PLoS Comput. Biol., 2009

Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach.
IEEE Trans. Pattern Anal. Mach. Intell., 2009

Bayesian learning of graphical vector autoregressions with unequal lag-lengths.
Mach. Learn., 2009

A Naive Bayes Classifier for Protein Function Prediction.
Silico Biol., 2009

Bayesian clustering and feature selection for cancer tissue samples.
BMC Bioinform., 2009

Bayesian Unsupervised Learning of DNA Regulatory Binding Regions.
Adv. Artif. Intell., 2009

Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy.
Adv. Data Anal. Classif., 2009

2008
Parallell interacting MCMC for learning of topologies of graphical models.
Data Min. Knowl. Discov., 2008

Bayesian spatial modeling of genetic population structure.
Comput. Stat., 2008

Bayesian modeling of recombination events in bacterial populations.
BMC Bioinform., 2008

Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations.
BMC Bioinform., 2008

2006
Bayesian model learning based on a parallel MCMC strategy.
Stat. Comput., 2006

Bayesian Model Learning Based on Predictive Entropy.
J. Log. Lang. Inf., 2006

Bayesian search of functionally divergent protein subgroups and their function specific residues.
Bioinform., 2006

2004
BAPS 2: enhanced possibilities for the analysis of genetic population structure.
Bioinform., 2004


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