Jukka Corander

104 papers A* 1A 1B 3C 1Misc 3Journal 82Unranked 12

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Misspecification-robust likelihood-free inference in high dimensions. Comput. Stat. Owen Thomas, Raquel Sá-Leão, Hermínia de Lencastre, Samuel Kaski, Jukka Corander, Henri Pesonen
2025	J	`jnl`	Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation. Comput. Stat. Data Anal. Henri Pesonen, Jukka Corander
2024	J	`jnl`	Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC. J. Mach. Learn. Res. Marko Järvenpää, Jukka Corander
2023	J	`jnl`	On predictive inference for intractable models via approximate Bayesian computation. Stat. Comput. Marko Järvenpää, Jukka Corander
2023	J	`jnl`	Stochastic cluster embedding. Stat. Comput. Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander
2022	J	`jnl`	Identification of multiplicatively acting modulatory mutational signatures in cancer. BMC Bioinform. Dovydas Kiciatovas, Qingli Guo, Miika Kailas, Henri Pesonen, Jukka Corander, Samuel Kaski, Esa Pitkänen, Ville Mustonen
2022	J	`jnl`	Likelihood-free Model Choice for Simulator-based Models with the Jensen-Shannon Divergence. CoRR Jukka Corander, Ulpu Remes, Timo Koski
2022	J	`jnl`	Likelihood-free inference with deep Gaussian processes. Comput. Stat. Data Anal. Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski
2022	J	`jnl`	Nonparametric likelihood-free inference with Jensen-Shannon divergence for simulator-based models with categorical output. CoRR Jukka Corander, Ulpu Remes, Ida Holopainen, Timo Koski
2021	J	`jnl`	Boosting heritability: estimating the genetic component of phenotypic variation with multiple sample splitting. BMC Bioinform. The Tien Mai, Paul Turner, Jukka Corander
2021	J	`jnl`	High-dimensional structure learning of sparse vector autoregressive models using fractional marginal pseudo-likelihood. Stat. Comput. Kimmo Suotsalo, Yingying Xu, Jukka Corander, Johan Pensar
2021	J	`jnl`	On the Jensen-Shannon divergence and the variation distance for categorical probability distributions. Kybernetika Jukka Corander, Ulpu Remes, Timo Koski
2021	J	`jnl`	Stochastic Cluster Embedding. CoRR Zhirong Yang, Yuwei Chen, Denis Sedov, Samuel Kaski, Jukka Corander
2021	J	`jnl`	T-SNE Is Not Optimized to Reveal Clusters in Data. CoRR Zhirong Yang, Yuwei Chen, Jukka Corander
2020	J	`jnl`	High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study. Comput. Stat. Data Anal. Johan Pensar, Yingying Xu, Santeri Puranen, Maiju Pesonen, Yoshiyuki Kabashima, Jukka Corander
2020	J	`jnl`	Likelihood-Free Inference with Deep Gaussian Processes. CoRR Alexander Aushev, Henri Pesonen, Markus Heinonen, Jukka Corander, Samuel Kaski
2020	J	`jnl`	gplas: a comprehensive tool for plasmid analysis using short-read graphs. Bioinform. Sergio Arredondo-Alonso, Martin Bootsma, Yaïr Hein, Malbert R. C. Rogers, Jukka Corander, Rob J. L. Willems, Anita C. Schürch
2019	J	`jnl`	A logical approach to context-specific independence. Ann. Pure Appl. Log. Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen
2019	J	`jnl`	Doubly Stochastic Neighbor Embedding on Spheres. Pattern Recognit. Lett. Yao Lu, Jukka Corander, Zhirong Yang
2019	J	`jnl`	High-dimensional structure learning of binary pairwise Markov networks: A comparative numerical study. CoRR Johan Pensar, Yingying Xu, Santeri Puranen, Maiju Pesonen, Yoshiyuki Kabashima, Jukka Corander
2019	—	`conf`	Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure. CIBB The Tien Mai, Leiv Rønneberg, Zhi Zhao, Manuela Zucknick, Jukka Corander
2019	J	`jnl`	Learning pairwise Markov network structures using correlation neighborhoods. CoRR Juri Kuronen, Jukka Corander, Johan Pensar
2018	J	`jnl`	Bacmeta: simulator for genomic evolution in bacterial metapopulations. Bioinform. Aleksi Sipola, Pekka Marttinen, Jukka Corander
2018	J	`jnl`	ELFI: Engine for Likelihood-Free Inference. J. Mach. Learn. Res. Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Pekka Marttinen, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski
2018	J	`jnl`	Kpax3: Bayesian bi-clustering of large sequence datasets. Bioinform. Alberto Pessia, Jukka Corander
2018	J	`jnl`	Likelihood-free inference via classification. Stat. Comput. Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski, Jukka Corander
2018	—	`conf`	Structure Learning for Bayesian Networks over Labeled DAGs. PGM Antti Hyttinen, Johan Pensar, Juha Kontinen, Jukka Corander
2018	J	`jnl`	pyseer: a comprehensive tool for microbial pangenome-wide association studies. Bioinform. John A. Lees, Marco Galardini, Stephen D. Bentley, Jeffrey N. Weiser, Jukka Corander
2017	J	`jnl`	Asymptotic Analysis of Rayleigh Product Channels: A Free Probability Approach. IEEE Trans. Inf. Theory Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander
2017	J	`jnl`	ELFI: Engine for Likelihood Free Inference. CoRR Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö, Kusti Skytén, Marko Järvenpää, Michael U. Gutmann, Aki Vehtari, Jukka Corander, Samuel Kaski
2017	J	`jnl`	From Random Matrix Theory to Coding Theory: Volume of a Metric Ball in Unitary Group. IEEE Trans. Inf. Theory Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen
2017	A*	`conf`	Inferring Cognitive Models from Data using Approximate Bayesian Computation. CHI Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta
2017	J	`jnl`	Layered adaptive importance sampling. Stat. Comput. Luca Martino, Victor Elvira, David Luengo, Jukka Corander
2017	J	`jnl`	Learning Gaussian graphical models with fractional marginal pseudo-likelihood. Int. J. Approx. Reason. Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
2017	J	`jnl`	Learning discrete decomposable graphical models via constraint optimization. Stat. Comput. Tomi Janhunen, Martin Gebser, Jussi Rintanen, Henrik J. Nyman, Johan Pensar, Jukka Corander
2016	C	`conf`	A Logical Approach to Context-Specific Independence. WoLLIC Jukka Corander, Antti Hyttinen, Juha Kontinen, Johan Pensar, Jouko Väänänen
2016	J	`jnl`	An object oriented Python interface for atomistic simulations. Comput. Phys. Commun. Teemu Hynninen, Lauri Himanen, V. Parkkinen, T. Musso, Jukka Corander, Adam S. Foster
2016	—	`conf`	Analysis of a privacy-preserving PCA algorithm using random matrix theory. GlobalSIP Lu Wei, Anand D. Sarwate, Jukka Corander, Alfred O. Hero III, Vahid Tarokh
2016	J	`jnl`	Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models. J. Mach. Learn. Res. Michael U. Gutmann, Jukka Corander
2016	—	`ch.`	Context-Specific and Local Independence in Markovian Dependence Structures. Dependence Logic Henrik J. Nyman, Johan Pensar, Jukka Corander
2016	J	`jnl`	Context-specific independence in graphical log-linear models. Comput. Stat. Henrik J. Nyman, Johan Pensar, Timo Koski, Jukka Corander
2016	J	`jnl`	Doubly Stochastic Neighbor Embedding on Spheres. CoRR Yao Lu, Zhirong Yang, Jukka Corander
2016	—	`conf`	Fast nearest neighbor search through sparse random projections and voting. IEEE BigData Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Elias Jaasaari, Risto Tuomainen, Liang Wang, Jukka Corander, Teemu Roos
2016	J	`jnl`	Inverse Modeling of Complex Interactive Behavior with ABC. CoRR Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes, Jukka Corander, Samuel Kaski, Antti Oulasvirta
2016	J	`jnl`	Learning Gaussian Graphical Models With Fractional Marginal Pseudo-likelihood. CoRR Janne Leppä-aho, Johan Pensar, Teemu Roos, Jukka Corander
2016	J	`jnl`	Low-Rank Doubly Stochastic Matrix Decomposition for Cluster Analysis. J. Mach. Learn. Res. Zhirong Yang, Jukka Corander, Erkki Oja
2016	J	`jnl`	Marginal and simultaneous predictive classification using stratified graphical models. Adv. Data Anal. Classif. Henrik J. Nyman, Jie Xiong, Johan Pensar, Jukka Corander
2016	J	`jnl`	On the inconsistency of ℓ CoRR Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela
2016	J	`jnl`	On the inconsistency of ℓ 1-penalised sparse precision matrix estimation. BMC Bioinform. Otte Heinävaara, Janne Leppä-aho, Jukka Corander, Antti Honkela
2016	J	`jnl`	Orthogonal parallel MCMC methods for sampling and optimization. Digit. Signal Process. Luca Martino, Víctor Elvira, David Luengo, Jukka Corander, Francisco Louzada
2016	J	`jnl`	Simultaneous Predictive Gaussian Classifiers. J. Classif. Yaqiong Cui, Jukka Sirén, Timo Koski, Jukka Corander
2016	J	`jnl`	The role of local partial independence in learning of Bayesian networks. Int. J. Approx. Reason. Johan Pensar, Henrik J. Nyman, Jarno Lintusaari, Jukka Corander
2016	J	`jnl`	Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds. IEEE Trans. Inf. Theory Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander
2015	J	`jnl`	A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type. IEEE Trans. Pattern Anal. Mach. Intell. Paul Blomstedt, Jing Tang, Jie Xiong, Christian Granlund, Jukka Corander
2015	J	`jnl`	A fast universal self-tuned sampler within Gibbs sampling. Digit. Signal Process. Luca Martino, H. Yang, David Luengo, Juho Kanniainen, Jukka Corander
2015	Misc	`conf`	A gradient adaptive population importance sampler. ICASSP Víctor Elvira, Luca Martino, David Luengo, Jukka Corander
2015	J	`jnl`	Adaptive importance sampling in signal processing. Digit. Signal Process. Mónica F. Bugallo, Luca Martino, Jukka Corander
2015	J	`jnl`	An Adaptive Population Importance Sampler: Learning From Uncertainty. IEEE Trans. Signal Process. Luca Martino, Victor Elvira, David Luengo, Jukka Corander
2015	—	`conf`	Denoising Cluster Analysis. ICONIP (3) Ruqi Zhang, Zhirong Yang, Jukka Corander
2015	J	`jnl`	Fast k-NN search. CoRR Ville Hyvönen, Teemu Pitkänen, Sotiris K. Tasoulis, Liang Wang, Teemu Roos, Jukka Corander
2015	J	`jnl`	From Random Matrix Theory to Coding Theory: Volume of a Metric Ball in Unitary Group. CoRR Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen
2015	J	`jnl`	Labeled directed acyclic graphs: a generalization of context-specific independence in directed graphical models. Data Min. Knowl. Discov. Johan Pensar, Henrik J. Nyman, Timo Koski, Jukka Corander
2015	J	`jnl`	Layered Adaptive Importance Sampling. CoRR Luca Martino, Victor Elvira, David Luengo, Jukka Corander
2015	J	`jnl`	On the Outage Capacity of Orthogonal Space-Time Block Codes Over Multi-Cluster Scattering MIMO Channels. IEEE Trans. Commun. Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco
2015	—	`conf`	On the exact volume of metric balls in complex Grassmann manifolds. ITW Fall Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander
2015	B	`conf`	On the finite-SNR Diversity-Multiplexing Tradeoff in large Rayleigh product channels. ISIT Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander
2015	B	`conf`	On the volume of a metric ball in unitary group. ISIT Lu Wei, Renaud-Alexandre Pitaval, Jukka Corander, Olav Tirkkonen
2015	J	`jnl`	Outage Capacity of Rayleigh Product Channels: a Free Probability Approach. CoRR Zhong Zheng, Lu Wei, Roland Speicher, Ralf R. Müller, Jyri Hämäläinen, Jukka Corander
2015	—	`conf`	Parallel interacting Markov adaptive importance sampling. EUSIPCO Luca Martino, Victor Elvira, David Luengo, Jukka Corander
2015	Misc	`conf`	Smelly parallel MCMC chains. ICASSP Luca Martino, Víctor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander
2015	J	`jnl`	Volume of Metric Balls in High-Dimensional Complex Grassmann Manifolds. CoRR Renaud-Alexandre Pitaval, Lu Wei, Olav Tirkkonen, Jukka Corander
2014	J	`jnl`	Addition Chains Meet Postage Stamps: Reducing the Number of Multiplications. J. Integer Seq. Jukka Kohonen, Jukka Corander
2014	Misc	`conf`	An adaptive population importance sampler. ICASSP Luca Martino, Victor Elvira, David Luengo, Jukka Corander
2014	J	`jnl`	On the Outage Capacity of Orthogonal Space-time Block Codes Over Multi-cluster Scattering MIMO Channels. CoRR Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco
2014	—	`conf`	Orthogonal MCMC algorithms. SSP Luca Martino, Victor Elvira, David Luengo, Antonio Artés-Rodríguez, Jukka Corander
2014	B	`conf`	Outage capacity of OSTBCs over pico-cellular MIMO channels. ISIT Lu Wei, Zhong Zheng, Jukka Corander, Giorgio Taricco
2014	A	`conf`	Preface. AISTATS Samuel Kaski, Jukka Corander
2014	—	`conf`	Random projection based clustering for population genomics. IEEE BigData Sotiris K. Tasoulis, Lu Cheng, Niko Välimäki, Nicholas J. Croucher, Simon R. Harris, William P. Hanage, Teemu Roos, Jukka Corander
2014	J	`jnl`	SEK: sparsity exploiting Bioinform. Saikat Chatterjee, David Koslicki, Siyuan Dong, Nicolas Innocenti, Lu Cheng, Yueheng Lan, Mikko Vehkaperä, Mikael Skoglund, Lars K. Rasmussen, Erik Aurell, Jukka Corander
2013	J	`jnl`	Approximate Bayesian Computation. PLoS Comput. Biol. Mikael Sunnåker, Alberto Giovanni Busetto, Elina Numminen, Jukka Corander, Matthieu Foll, Christophe Dessimoz
2013	J	`jnl`	Have I seen you before? Principles of Bayesian predictive classification revisited. Stat. Comput. Jukka Corander, Yaqiong Cui, Timo Koski, Jukka Sirén
2013	J	`jnl`	Labeled Directed Acyclic Graphs: a generalization of context-specific independence in directed graphical models. CoRR Johan Pensar, Henrik J. Nyman, Timo Koski, Jukka Corander
2013	—	`conf`	Learning Chordal Markov Networks by Constraint Satisfaction. NIPS Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar
2013	J	`jnl`	Learning Chordal Markov Networks by Constraint Satisfaction. CoRR Jukka Corander, Tomi Janhunen, Jussi Rintanen, Henrik J. Nyman, Johan Pensar
2012	—	`conf`	Bayesian Block-Diagonal Predictive Classifier for Gaussian Data. SMPS Jukka Corander, Timo Koski, Tatjana Pavlenko, Annika Tillander
2011	J	`jnl`	Bayesian semi-supervised classification of bacterial samples using MLST databases. BMC Bioinform. Lu Cheng, Thomas R. Connor, David M. Aanensen, Brian G. Spratt, Jukka Corander
2011	—	`conf`	Inductive Inference and Partition Exchangeability in Classification. Algorithmic Probability and Friends Jukka Corander, Yaqiong Cui, Timo Koski
2010	J	`jnl`	Efficient Bayesian approach for multilocus association mapping including gene-gene interactions. BMC Bioinform. Pekka Marttinen, Jukka Corander
2010	J	`jnl`	Learning Genetic Population Structures Using Minimization of Stochastic Complexity. Entropy Jukka Corander, Mats Gyllenberg, Timo Koski
2009	J	`jnl`	A Naive Bayes Classifier for Protein Function Prediction. Silico Biol. Jukka Kohonen, Sarish Talikota, Jukka Corander, Petri Auvinen, Elja Arjas
2009	J	`jnl`	Bayesian Clustering of Fuzzy Feature Vectors Using a Quasi-Likelihood Approach. IEEE Trans. Pattern Anal. Mach. Intell. Pekka Marttinen, Jing Tang, Bernard De Baets, Peter Dawyndt, Jukka Corander
2009	J	`jnl`	Bayesian Unsupervised Learning of DNA Regulatory Binding Regions. Adv. Artif. Intell. Jukka Corander, Magnus Ekdahl, Timo Koski
2009	J	`jnl`	Bayesian clustering and feature selection for cancer tissue samples. BMC Bioinform. Pekka Marttinen, Samuel Myllykangas, Jukka Corander
2009	J	`jnl`	Bayesian learning of graphical vector autoregressions with unequal lag-lengths. Mach. Learn. Pekka Marttinen, Jukka Corander
2009	J	`jnl`	Bayesian unsupervised classification framework based on stochastic partitions of data and a parallel search strategy. Adv. Data Anal. Classif. Jukka Corander, Mats Gyllenberg, Timo Koski
2009	J	`jnl`	Identifying Currents in the Gene Pool for Bacterial Populations Using an Integrative Approach. PLoS Comput. Biol. Jing Tang, William P. Hanage, Christophe Fraser, Jukka Corander
2008	J	`jnl`	Bayesian modeling of recombination events in bacterial populations. BMC Bioinform. Pekka Marttinen, Adam Baldwin, William P. Hanage, Chris Dowson, Eshwar Mahenthiralingam, Jukka Corander
2008	J	`jnl`	Bayesian spatial modeling of genetic population structure. Comput. Stat. Jukka Corander, Jukka Sirén, Elja Arjas
2008	J	`jnl`	Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinform. Jukka Corander, Pekka Marttinen, Jukka Sirén, Jing Tang
2008	J	`jnl`	Parallell interacting MCMC for learning of topologies of graphical models. Data Min. Knowl. Discov. Jukka Corander, Magnus Ekdahl, Timo Koski
2006	J	`jnl`	Bayesian Model Learning Based on Predictive Entropy. J. Log. Lang. Inf. Jukka Corander, Pekka Marttinen
2006	J	`jnl`	Bayesian model learning based on a parallel MCMC strategy. Stat. Comput. Jukka Corander, Mats Gyllenberg, Timo Koski
2006	J	`jnl`	Bayesian search of functionally divergent protein subgroups and their function specific residues. Bioinform. Pekka Marttinen, Jukka Corander, Petri Törönen, Liisa Holm
2004	J	`jnl`	BAPS 2: enhanced possibilities for the analysis of genetic population structure. Bioinform. Jukka Corander, Patrik Waldmann, Pekka Marttinen, Mikko J. Sillanpää