Samuel Kaski

Samuel Kaski, Samuel Kaski, 2001, Neural Networks for Signal Processing XI: Proceedings of the 2001 IEEE Signal Processing Society Workshop (IEEE Cat. No.01TH8584).

Self-organizing map-based discovery and visualization of human endogenous retroviral

Samuel Kaski, Merja Oja, Göran O. Sperber, 2005 .

Associative Clustering for Exploring Dependencies between Functional Genomics Data Sets

Samuel Kaski, Janne Nikkila, Janne Sinkkonen, 2005, TCBB.

Probabilistic modeling and machine learning in structural and systems biology

Juho Rousu, Samuel Kaski, Esko Ukkonen, 2007, BMC Bioinformatics.

SciNet: a system for browsing scientific literature through keyword manipulation

Dorota Glowacka, Samuel Kaski, Tuukka Ruotsalo, 2013, IUI '13 Companion.

Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI-16)

Samuel Kaski, Shanfeng Zhu, Makoto Yamada, 2016, IJCAI 2016.

Retrieval of Experiments by Efficient Estimation of Marginal Likelihood pdf

John Shawe-Taylor, Samuel Kaski, Sohan Seth, 2014, ArXiv.

ICANN/PASCAL2 Challenge: MEG Mind Reading — Overview and Results

Samuel Kaski, Arto Klami, Lauri Parkkonen, 2012 .

Machine learning for signal processing 2010

Tapani Raiko, Samuel Kaski, Jaakko Peltonen, 2012, Neurocomputing.

Methods for interpreting a self-organized map in data analysis

Samuel Kaski, Teuvo Kohonen, Janne Nikkilä, 1998, ESANN.

Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays

Tero Aittokallio, Samuel Kaski, Leo Lahti, 2011, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Interactive intent modeling

Samuel Kaski, Tuukka Ruotsalo, Giulio Jacucci, 2014, Commun. ACM.

Two-Way Latent Grouping Model for User Preference Prediction

Samuel Kaski, Kai Puolamäki, Janne Sinkkonen, 2005, UAI.

Interactive Intent Modeling for Exploratory Search

Dorota Glowacka, Samuel Kaski, Jaakko Peltonen, 2018, ACM Trans. Inf. Syst..

Automatic Choice of Control Measurements

Samuel Kaski, Gayle Leen, David R. Hardoon, 2009, ACML.

Learning spectrograms with convolutional spectral kernels

Samuel Kaski, Markus Heinonen, Zheyang Shen, 2020, AISTATS.

Associative Clustering by Maximizing a Bayes Factor

Samuel Kaski, Janne Sinkkonen, Leo Lahti, 2003 .

ICML 2008, Twenty-Fifth International Conference on Machine Learning

Samuel Kaski, Kai Puolamäki, Antti Ajanki, 2008 .

Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization

Jarkko Venna, Samuel Kaski, Jaakko Peltonen, 2010, J. Mach. Learn. Res..

Interactive Intent Modeling from Multiple Feedback Domains

Dorota Glowacka, Samuel Kaski, Pedram Daee, 2016, IUI.

Regularized discriminative clustering

Samuel Kaski, Arto Klami, Janne Sinkkonen, 2003, 2003 IEEE XIII Workshop on Neural Networks for Signal Processing (IEEE Cat. No.03TH8718).

Bayesian exponential family projections for coupled data sources

Samuel Kaski, Seppo Virtanen, Arto Klami, 2010, UAI.

Bankruptcy analysis with self-organizing maps in learning metrics

Samuel Kaski, Jaakko Peltonen, Janne Sinkkonen, 2001, IEEE Trans. Neural Networks.

Neural networks and machine learning in bioinformatics - theory and applications

Thomas Villmann, Barbara Hammer, Samuel Kaski, 2006, ESANN.

Representation transfer for differentially private drug sensitivity prediction

Antti Honkela, Samuel Kaski, Teppo Niinimaki, 2019, Bioinform..

Compression of vector quantization code sequences based on code frequencies and spatial redundancies

Samuel Kaski, Jari Kangas, 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

R EG U L AR I Z ED DISC R I M I NATIVE CLUSTERING

Samuel Kaski, Janne Sinkkonen, Samuel Kaski, 2003 .

Computational Statistics Approaches to Study Metabolic Syndrome

Samuel Kaski, Ilkka Huopaniemi, Samuel Kaski, 2014 .

Introduction to the special issue on mining and learning with graphs

Jennifer Neville, S. V. N. Vishwanathan, Samuel Kaski, 2010, Machine Learning.

Exploratory modeling of yeast stress response and its regulation with gcca and associative clustering

Samuel Kaski, Christophe Roos, Janne Nikkilä, 2005, Int. J. Neural Syst..

Localized Lasso for High-Dimensional Regression

John Shawe-Taylor, Koh Takeuchi, Makoto Yamada, 2016, AISTATS.

Discriminative Clustering: Optimal Contingency Tables by Learning Metrics

Samuel Kaski, Janne Sinkkonen, Janne Nikkilä, 2002, ECML.

Distributed Bayesian matrix factorization with limited communication

Samuel Kaski, Pekka Parviainen, Paul Blomstedt, 2017, Machine Learning.

Visualized Atlas of a Gene Expression Databank

Jarkko Venna, Samuel Kaski, Samuel Kaski, 2005 .

Information Retrieval Perspective to Interactive Data Visualization

Samuel Kaski, Jaakko Peltonen, Max Sandholm, 2013, EuroVis.

Group Factor Analysis

Samuel Kaski, Arto Klami, Seppo Virtanen, 2014, IEEE Transactions on Neural Networks and Learning Systems.

Automatic Coloring of Data According to Its Cluster Structure

Jarkko Venna, Samuel Kaski, Teuvo Kohonen, 1997 .

Modelling Human Decision-making based on Aggregate Observation Data

Samuel Kaski, Antti Kangasrääsiö, 2017, ICML 2017.

Newsgroup Exploration with WEBSOM Method and Browsing Interface

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996 .

Workshop on Bayesian Optimization in Academia and Industry, Neural Information Processing Systems, NIPS2014, 8-13 December, Montreal, Canada

Dorota Glowacka, Samuel Kaski, Jaakko Peltonen, 2014 .

Variational zero-inflated Gaussian processes with sparse kernels

Samuel Kaski, Markus Heinonen, Pashupati Hegde, 2018, UAI.

Predicting term-relevance from brain signals

Samuel Kaski, Manuel J. A. Eugster, Tuukka Ruotsalo, 2014, SIGIR.

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs

Krister Wennerberg, Samuel Kaski, Ali Faisal, 2011, BMC Bioinformatics.

Ranking algorithms for implicit feedback

Alex Po Leung, Kitsuchart Pasupa, Peter Auer, 2009 .

Convex Factorization Machine for Toxicogenomics Prediction

Jianhui Chen, Samuel Kaski, Makoto Yamada, 2017, KDD.

Fast Discriminative Component Analysis for Comparing Examples

Samuel Kaski, Jacob Goldberger, Jaakko Peltonen, 2006 .

Browsing digital libraries with the aid of self-organizing maps

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996 .

Bayesian Multi-view Tensor Factorization

Samuel Kaski, Suleiman A. Khan, Samuel Kaski, 2014, ECML/PKDD.

Discriminative Clustering in Fisher Metrics

Samuel Kaski, Jarkko Salojärvi, Janne Sinkkonen, 2003 .

Multi-view kernel completion

Juho Rousu, Samuel Kaski, Sahely Bhadra, 2016, Machine Learning.

Variational Bayesian Mixture of Robust CCA Models

Samuel Kaski, Arto Klami, Jaakko Viinikanoja, 2010, ECML/PKDD.

Generative Modeling for Maximizing Precision and Recall in Information Visualization

Samuel Kaski, Jaakko Peltonen, Samuel Kaski, 2011, AISTATS.

Nonlinear Dimensionality Reduction as Information Retrieval

Jarkko Venna, Samuel Kaski, Samuel Kaski, 2007, AISTATS.

Probabilistic retrieval and visualization of biologically relevant microarray experiments

Samuel Kaski, Ali Faisal, Alvis Brazma, 2009, Bioinform..

Information Retrieval by Inferring Implicit Queries from Eye Movements

John Shawe-Taylor, Samuel Kaski, Kai Puolamäki, 2007, AISTATS.

RPA: Probabilistic analysis of probe performance and robust summarization pdf

Tero Aittokallio, Samuel Kaski, Laura L. Elo, 2011, ArXiv.

Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression

Samuel Kaski, Pedram Daee, Tomi Peltola, 2017, IAL@PKDD/ECML.

Differentially private Bayesian learning on distributed data

Antti Honkela, Sasu Tarkoma, Eemil Lagerspetz, 2017, NIPS.

Learning relevance from natural eye movements in pervasive interfaces

Samuel Kaski, Melih Kandemir, 2012, ICMI '12.

Ubiquitous Contextual Information Access with Proactive Retrieval and Augmentation

Jorma Laaksonen, Mikko Kurimo, Markus Koskela, 2009 .

Multivariate multi-way analysis of multi-source data

Matej Oresic, Samuel Kaski, Ilkka Huopaniemi, 2010, Bioinform..

Kernelized Bayesian Matrix Factorization

Samuel Kaski, Mehmet Gönen, Suleiman A. Khan, 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

COMPUTATIONAL BIOLOGY AND BIOINFORMATICS

Cigdem Demir, Alexander Schliep, John Hawkins, 2005 .

Probabilistic Formulation of the Take The Best Heuristic pdf

Samuel Kaski, Jussi Jokinen, Tomi Peltola, 2019, CogSci.

Exploratory and contextual search with interactive intent modelling

Samuel Kaski, Samuel Kaski, 2014 .

Bayesian Group Factor Analysis

Samuel Kaski, Seppo Virtanen, Arto Klami, 2012, AISTATS.

Active Learning for Decision-Making from Imbalanced Observational Data

Aki Vehtari, Suchi Saria, Samuel Kaski, 2019, ICML.

The rocky road to personalized medicine: computational and statistical challenges.

Jukka Corander, Tero Aittokallio, Samuel Kaski, 2012, Personalized medicine.

Clustering Gene Expression Data by Mutual Information with Gene Function

Samuel Kaski, Janne Sinkkonen, Janne Nikkilä, 2001, ICANN.

Visualizations relevant to the user by multi-view latent variable factorization

Samuel Kaski, Seppo Virtanen, Homayun Afrabandpey, 2015, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Interactive Modeling of Concept Drift and Errors in Relevance Feedback

Dorota Glowacka, Samuel Kaski, Yi Chen, 2016, UMAP.

2002 Special Issue Analysis and visualization of gene expression data using

Jarkko Venna, Samuel Kaski, Garry Wong, 2002 .

Proceedings of the 22nd ACM international conference on Conference on information & knowledge management

Samuel Kaski, Jaakko Peltonen, Manuel J. A. Eugster, 2013 .

Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets

Samuel Kaski, Homayun Afrabandpey, Tomi Peltola, 2019, IJCAI.

The Twenty-Sixth Conference on Uncertainty in Artificial Intelligence (2010)

Samuel Kaski, Arto Klami, Seppo Virtanen, 2010 .

The IEEE International Workshop on Machine Learning for Signal Processing XVIII

Samuel Kaski, José Caldas, Samuel Kaski, 2008 .

Electronic editor: automatic content-based sequential compilation of newspaper articles

Christer Bäckström, Ville Ollikainen, Samuel Kaski, 2002, Neurocomputing.

Discovering heritable modes of MEG spectral power

Riitta Salmelin, Samuel Kaski, Eemeli Leppäaho, 2019, Human brain mapping.

Extracting relevance and affect information from physiological text annotation

Samuel Kaski, Manuel J. A. Eugster, Tuukka Ruotsalo, 2016, User Modeling and User-Adapted Interaction.

User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction

Aki Vehtari, Samuel Kaski, Pedram Daee, 2017, IUI.

Learning Image Relations with Contrast Association Networks

Yao Lu, Samuel Kaski, Juho Kannala, 2017, 2019 International Joint Conference on Neural Networks (IJCNN).

Comparing Self-Organizing Maps

Samuel Kaski, Krista Lagus, 1996, ICANN.

WEBSOM -- A Status Report

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996 .

Supporting exploratory search tasks with interactive user modeling

Dorota Glowacka, Samuel Kaski, Antti Oulasvirta, 2013, ASIST.

Self-Organizing Maps of Large Document Collections

Timo Honkela, Samuel Kaski, Krista Lagus, 1998 .

Deep learning with differential Gaussian process flows pdf

Samuel Kaski, Markus Heinonen, Harri Lähdesmäki, 2018, AISTATS.

User models from implicit feedback for proactive information retrieval

Samuel Kaski, Ilpo Kojo, Petri Myllymäki, 2005 .

Exploring Peripheral Physiology as a Predictor of Perceived Relevance in Information Retrieval

Samuel Kaski, Manuel J. A. Eugster, Tuukka Ruotsalo, 2015, IUI.

A Latent Feature Model Approach to Biclustering

Samuel Kaski, José Caldas, Samuel Kaski, 2016, Int. J. Knowl. Discov. Bioinform..

Associative Clustering (AC): Technical Details

Samuel Kaski, Janne Sinkkonen, Leo Lahti, 2005 .

Proactive information retrieval by monitoring eye movements

Samuel Kaski, 2005 .

GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis

Samuel Kaski, Eemeli Leppäaho, Muhammad Ammad-ud-din, 2016, J. Mach. Learn. Res..

Scalable Probabilistic Matrix Factorization with Graph-Based Priors pdf

Samuel Kaski, Jaakko Peltonen, Hiroshi Mamitsuka, 2019, AAAI.

Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge

Samuel Kaski, Chen He, Giulio Jacucci, 2017, Bioinform..

Proceedings of KRBIO05, Symposium on Knowledge Representation in Bioinformatics, Espoo, Finland, June 15-17, 2005

Samuel Kaski, Jaakko Hollmén, Catherine Bounsaythip, 2005 .

ICASSP 09, the International Conference on Acoustics, Speech, and Signal Processing

Samuel Kaski, Arto Klami, Eerika Savia, 2009 .

Self-Organizing Maps

Samuel Kaski, Samuel Kaski, 2017, Encyclopedia of Machine Learning and Data Mining.

Tips for Processing and Color-coding of Self-Organizing Maps

Samuel Kaski, Teuvo Kohonen, T. Kohonen, 1998 .

Dealing with Concept Drift in Exploratory Search: An Interactive Bayesian Approach

Dorota Glowacka, Samuel Kaski, Yi Chen, 2016, IUI Companion.

Bayesian Canonical correlation analysis

Samuel Kaski, Seppo Virtanen, Arto Klami, 2013, J. Mach. Learn. Res..

A Block Model Suitable for Sparse Graphs

Samuel Kaski, Janne Sinkkonen, Juuso Parkkinen, 2009 .

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings

Samuel Kaski, Markus Heinonen, Sami Remes, 2017, ACML.

Dependency detection with similarity constraints

Samuel Kaski, Leo Lahti, Samuel Myllykangas, 2009, 2009 IEEE International Workshop on Machine Learning for Signal Processing.

Graph visualization with latent variable models

Samuel Kaski, Jaakko Peltonen, Kristian Nybo, 2010, MLG '10.

Retrieval of Experiments by Efficient Comparison of Marginal Likelihoods

John Shawe-Taylor, Samuel Kaski, Sohan Seth, 2014, ICONIP.

Hierarchical Generative Biclustering for MicroRNA Expression Analysis

Samuel Kaski, José Caldas, Samuel Kaski, 2010, RECOMB.

Discriminative clustering

Samuel Kaski, Arto Klami, Janne Sinkkonen, 2005, Neurocomputing.

Learning when only some of the training data are from the same distribution as test data

Samuel Kaski, Jaakko Peltonen, 2006 .

Informative Discriminant Analysis

Samuel Kaski, Jaakko Peltonen, 2003, ICML.

An augmented reality interface to contextual information

Jorma Laaksonen, Mikko Kurimo, Markus Koskela, 2011, Virtual Reality.

Matching samples of multiple views

Matej Oresic, Samuel Kaski, Arto Klami, 2011, Data Mining and Knowledge Discovery.

Pinview: Implicit Feedback in Content-Based Image Retrieval

Jorma Laaksonen, Alex Po Leung, John Shawe-Taylor, 2010, WAPA.

Local dependent components

Samuel Kaski, Arto Klami, Samuel Kaski, 2007, ICML '07.

Multiple Output Regression with Latent Noise

Matti Pirinen, Samuel Kaski, Jussi Gillberg, 2014, J. Mach. Learn. Res..

Metabolic Regulation in Progression to Autoimmune Diabetes

Matej Oresic, Samuel Kaski, Olli Simell, 2011, PLoS Comput. Biol..

International Conference on Intelligent User Interfaces (IUI'15), Atlanta, GA, 29.3.2015

Dorota Glowacka, Samuel Kaski, Antti Kangasrääsiö, 2015 .

Bayesian multi-tensor factorization

Samuel Kaski, Eemeli Leppäaho, Suleiman A. Khan, 2016, Machine Learning.

Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis

Krister Wennerberg, Samuel Kaski, Seppo Virtanen, 2013, Bioinform..

Inferring object relevance from gaze in dynamic scenes

Samuel Kaski, Melih Kandemir, Veli-Matti Saarinen, 2010, ETRA.

ELFI, a software package for likelihood-free inference

Aki Vehtari, Jukka Corander, Samuel Kaski, 2017, ICML 2017.

Relevant subtask learning by constrained mixture models

Samuel Kaski, Jaakko Peltonen, Yusuf Yaslan, 2010, Intell. Data Anal..

A Topography-Preserving Latent Variable Model with Learning Metrics

Samuel Kaski, Janne Sinkkonen, Samuel Kaski, 2001, WSOM.

Cross-Species Translation of Multi-way Biomarkers

Matej Oresic, Samuel Kaski, Ilkka Huopaniemi, 2011, ICANN.

Self-Organized Formation of Various Invariant-Feature Filters in the Adaptive-Subspace SOM

Samuel Kaski, Teuvo Kohonen, Harri Lappalainen, 1997, Neural Computation.

Samuel's Checkers Player

Risto Miikkulainen, Scott Sanner, Kristian Kersting, 2010, Encyclopedia of Machine Learning.

Advances in Independent Component Analysis and Learning Machines

Jouko Lampinen, Jorma Laaksonen, Samuel Kaski, 2015 .

Neljännesvuosisata Hatutusta: Hahmontunnistustutkimus Suomessa 1977-2002

Samuel Kaski, Jukka Iivarinen, Erkki Oja, 2002 .

Discriminative clustering of text documents

Samuel Kaski, Jaakko Peltonen, Janne Sinkkonen, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Majorization-Minimization for Manifold Embedding

Samuel Kaski, Jaakko Peltonen, Zhirong Yang, 2015, AISTATS.

Bayesian CCA via Group Sparsity

Samuel Kaski, Seppo Virtanen, Arto Klami, 2011, ICML.

Multi-task and multi-view learning of user state

Samuel Kaski, Melih Kandemir, Arto Klami, 2014, Neurocomputing.

Preliminary Studies on Personalized Preference Prediction from Gaze in Comparing Visualizations

Jorma Laaksonen, Samuel Kaski, Jaakko Peltonen, 2016, ISVC.

Resolving outbreak dynamics using Approximate Bayesian Computation for stochastic birth-death models

Jukka Corander, Samuel Kaski, Michael U. Gutmann, 2017 .

Probabilistic drug connectivity mapping

Samuel Kaski, Juuso A. Parkkinen, Samuel Kaski, 2014, BMC Bioinformatics.

Associative clustering for exploring dependencies between functional genomics data sets

Samuel Kaski, Janne Sinkkonen, Leo Lahti, 2005, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Exploring Dependencies Between Yeast Stress Genes and Their Regulators

Samuel Kaski, Christophe Roos, Janne Nikkilä, 2004, IDEAL.

Non-Stationary Spectral Kernels

Samuel Kaski, Markus Heinonen, Sami Remes, 2017, NIPS.

Learning Metrics for Information Visualization

Samuel Kaski, Jaakko Peltonen, Arto Klami, 2003 .

Embarrassingly Parallel MCMC using Deep Invertible Transformations

Samuel Kaski, Diego Mesquita, Paul Blomstedt, 2019, UAI.

An Analysis of Generalization Error in Relevant Subtask Learning

Samuel Kaski, Keisuke Yamazaki, Samuel Kaski, 2008, ICONIP.

Integrating neurophysiologic relevance feedback in intent modeling for information retrieval

Samuel Kaski, Benjamin Blankertz, Luciano Gamberini, 2019, J. Assoc. Inf. Sci. Technol..

Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization

Tero Aittokallio, Samuel Kaski, Muhammad Ammad-ud-din, 2016, Bioinform..

Creating an Order in Digital Libraries with Self-Organizing Maps

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996 .

An information retrieval perspective on visualization of gene expression data with ontological annotation

Samuel Kaski, Jaakko Peltonen, Helena Aidos, 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.

Bayesian Solutions to the Label Switching Problem

Samuel Kaski, Kai Puolamäki, Samuel Kaski, 2009, IDA.

MediSyn: uncertainty-aware visualization of multiple biomedical datasets to support drug treatment selection

Tero Aittokallio, Samuel Kaski, Chen He, 2017 .

2001 IEEE Signal Processing Society Workshop, Neural Networks for Signal Processing XI, Falmouth, Massach., USA, Sept. 10-12, 2001

Samuel Kaski, Samuel Kaski, 2001 .

Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data

Makoto Yamada, Samuel Kaski, Chloé-Agathe Azencott, 2019, Bioinform..

Hierarchical Generative Biclustering for MicroRNA Expression Analysis

Samuel Kaski, José Caldas, 2011, J. Comput. Biol..

Global modeling of transcriptional responses in interaction networks

Samuel Kaski, Leo Lahti, Juha E. A. Knuuttila, 2010, Bioinform..

Artificial Neural Networks and Machine Learning - ICANN 2011 - 21st International Conference on Artificial Neural Networks, Espoo, Finland, June 14-17, 2011, Proceedings, Part I

Timo Honkela, Samuel Kaski, Mark Girolami, 2011, ICANN.

A Robust Convex Formulation for Ensemble Clustering

Samuel Kaski, Makoto Yamada, Hiroshi Mamitsuka, 2016, IJCAI.

Clustering Based on Conditional Distributions in an Auxiliary Space

Samuel Kaski, Janne Sinkkonen, Samuel Kaski, 2002, Neural Computation.

SciNet: Interactive Intent Modeling for Information Discovery

Dorota Glowacka, Samuel Kaski, Jaakko Peltonen, 2015, SIGIR.

Learning to rank images from eye movements

Kitsuchart Pasupa, Samuel Kaski, Steve R. Gunn, 2009, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops.

Supervised nonlinear dimensionality reduction by Neighbor Retrieval

Samuel Kaski, Jaakko Peltonen, Helena Aidos, 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

3043 Works that Have Been Based on the Self-Organizing Map (SOM) Method Developed by Kohonen

Samuel Kaski, Jari Kangas, Samuel Kaski, 1998 .

Exploration and retrieval of whole-metagenome sequencing samples

Antti Honkela, Samuel Kaski, Sohan Seth, 2013, Bioinform..

Neural Non-Stationary Spectral Kernel pdf

Samuel Kaski, Markus Heinonen, Sami Remes, 2018, ArXiv.

Majorization-Minimization for Manifold Embedding (Supplemental Document)

Samuel Kaski, Jaakko Peltonen, Z. Yang, 2015 .

Winner-take-all networks for physiological models of competitive learning

Samuel Kaski, Teuvo Kohonen, T. Kohonen, 1994, Neural Networks.

Latent grouping models for user preference prediction

Samuel Kaski, Kai Puolamäki, Eerika Savia, 2008, Machine Learning.

Fast dependent components for fMRI analysis

Samuel Kaski, Arto Klami, Eerika Savia, 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects pdf

Matti Pirinen, Samuel Kaski, Jussi Gillberg, 2013, ArXiv.

Using dependencies to pair samples for multi-view learning

Samuel Kaski, Arto Klami, Abhishek Tripathi, 2009, 2009 IEEE International Conference on Acoustics, Speech and Signal Processing.

Infinite factorization of multiple non-parametric views

Samuel Kaski, Simon Rogers, Mark A. Girolami, 2010, Machine Learning.

ICML 2016 Workshop on Computational Frameworks for Personalization

Dorota Glowacka, Samuel Kaski, Antti Kangasrääsiö, 2016 .

Visualizing the Clusters on the Self-Organizing Map

Samuel Kaski, Teuvo Kohonen, Jari Kangas, 1994 .

Directing exploratory search with interactive intent modeling

Dorota Glowacka, Samuel Kaski, Jaakko Peltonen, 2013, CIKM.

Stronger findings from mass spectral data through multi-peak modeling

Samuel Kaski, Simon Rogers, Tommi Suvitaival, 2014, BMC Bioinformatics.

Efficient differentially private learning improves drug sensitivity prediction

Antti Honkela, Samuel Kaski, Onur Dikmen, 2016, Biology Direct.

Two-way analysis of high-dimensional collinear data

Matej Oresic, Samuel Kaski, Ilkka Huopaniemi, 2009, Data Mining and Knowledge Discovery.

Integration of transcription factor binding and gene expression by associative clustering

Samuel Kaski, Christophe Roos, Janne Nikkilä, 2005 .

Two-Way Analysis of High-Dimensional Collinear Data

Matej Oresic, Samuel Kaski, Ilkka Huopaniemi, 2009, ECML/PKDD.

Clustering by Similarity in an Auxiliary Space

Samuel Kaski, Janne Sinkkonen, Samuel Kaski, 2000, IDEAL.

Data Visualization and Analysis with Self-Organizing Maps in Learning Metrics

Samuel Kaski, Jaakko Peltonen, Janne Sinkkonen, 2001, DaWaK.

Modelling-based experiment retrieval: A case study with gene expression clustering

Samuel Kaski, Sohan Seth, Alvis Brazma, 2015, Bioinform..

Sequential information bottleneck for finite data

Samuel Kaski, Jaakko Peltonen, Janne Sinkkonen, 2004, ICML.

Regression with n→1 by Expert Knowledge Elicitation

Samuel Kaski, Muhammad Ammad-ud-din, Marta Soare, 2016, 2016 15th IEEE International Conference on Machine Learning and Applications (ICMLA).

Automatic Content-based Sequential Ordering of Newspaper Articles for Electronic Books

Christer Bäckström, Ville Ollikainen, Samuel Kaski, 2000 .

Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation pdf

Samuel Kaski, Pedram Daee, Homayun Afrabandpey, 2017, ArXiv.

9th International Conference on Neural Information Processing (ICONIP'02), Singapore, November 18-22, 2002

Samuel Kaski, Janne Sinkkonen, Janne Peltonen, 2002 .

GaZIR: gaze-based zooming interface for image retrieval

Samuel Kaski, Arto Klami, László Kozma, 2009, ICMI-MLMI '09.

Harmonizable mixture kernels with variational Fourier features

Samuel Kaski, Markus Heinonen, Zheyang Shen, 2019, AISTATS.

Analysis and visualization of gene expression data using Self-Organizing Maps

Jarkko Venna, Samuel Kaski, Petri Törönen, 2002, Neural Networks.

Associative Clustering

Samuel Kaski, Janne Sinkkonen, Leo Lahti, 2004, ECML.

Comparison of visualization methods for an atlas of gene expression data sets

Jarkko Venna, Samuel Kaski, 2007 .

Non-parametric dependent components

Samuel Kaski, Arto Klami, 2005, Proceedings. (ICASSP '05). IEEE International Conference on Acoustics, Speech, and Signal Processing, 2005..

On Discriminative Joint Density Modeling

Samuel Kaski, Kai Puolamäki, Jarkko Salojärvi, 2005, ECML.

MediSyn: uncertainty-aware visualization of multiple biomedical datasets to support drug treatment selection

Tero Aittokallio, Samuel Kaski, Chen He, 2017, BMC Bioinformatics.

Mining massive document collections by the WEBSOM method

Samuel Kaski, Teuvo Kohonen, Krista Lagus, 2004, Inf. Sci..

WEBSOM - Self-organizing maps of document collections

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1998, Neurocomputing.

Learning from Relevant Tasks Only

Samuel Kaski, Jaakko Peltonen, 2007, ECML.

Very Large Two-Level SOM for the Browsing of Newsgroups

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996, ICANN.

Metrics that learn relevance

Samuel Kaski, Janne Sinkkonen, 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium.

Fast winner search for SOM-based monitoring and retrieval of high-dimensional data

Samuel Kaski, Samuel Kaski, 1999 .

Exploration of full-text databases with self-organizing maps

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Discriminative Clustering: Vector Quantization in Learning Metrics

Samuel Kaski, Janne Sinkkonen, Samuel Kaski, 2003 .

Probabilistic Proactive Timeline Browser

Samuel Kaski, Antti Ajanki, 2011, ICANN.

Learning More Accurate Metrics for Self-Organizing Maps

Samuel Kaski, Jaakko Peltonen, Arto Klami, 2002, ICANN.

Inferring Relevance from Eye Movements: Feature Extraction

Samuel Kaski, Kai Puolamäki, Ilpo Kojo, 2005 .

Adaptive timeline interface to personal history data

Jorma Laaksonen, Markus Koskela, Samuel Kaski, 2013, ICMI '13.

UMAP 2016 - Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization

Dorota Glowacka, Samuel Kaski, Yi Chen, 2016 .

Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction

Samuel Kaski, Pedram Daee, Tomi Peltola, 2016, Machine Learning.

Probabilistic approach to detecting dependencies between data sets

Samuel Kaski, Arto Klami, Samuel Kaski, 2008, Neurocomputing.

Variational Bayes Learning from Relevant Tasks Only

Samuel Kaski, Jaakko Peltonen, Yusuf Yaslan, 2008 .

Dimensionality reduction by random mapping: fast similarity computation for clustering

Samuel Kaski, Samuel Kaski, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo

Juho Rousu, Samuel Kaski, Markus Heinonen, 2015, AISTATS.

54th Session of the International Statistical Institute, Berlin, Germany, August 13-20, 2003

Samuel Kaski, Samuel Kaski, 2003 .

Self organization of a massive text document collection

Samuel Kaski, Teuvo Kohonen, Jarkko Salojärvi, 1999 .

Sparse group factor analysis for biclustering of multiple data sources

Samuel Kaski, Kerstin Bunte, Eemeli Leppäaho, 2015, Bioinform..

Analysis of magnetoencephalographic data with self-organizing maps

Riitta Salmelin, Samuel Kaski, K. Portin, 1993 .

Focused Multi-task Learning Using Gaussian Processes

Samuel Kaski, Jaakko Peltonen, Gayle Leen, 2011, ECML/PKDD.

Prediction of relevance of an image from a scan pattern

Kitsuchart Pasupa, Samuel Kaski, Arto Klami, 2008 .

Inferring Cognitive Models from Data using Approximate Bayesian Computation

Jukka Corander, Samuel Kaski, Antti Oulasvirta, 2016, CHI.

Dependencies between stimuli and spatially independent fMRI sources: Towards brain correlates of natural stimuli

Samuel Kaski, Jarkko Ylipaavalniemi, Ricardo Vigário, 2009, NeuroImage.

Grouping and visualizing human endogenous retroviruses by bootstrapping median self-organizing maps

Samuel Kaski, Merja Oja, Göran O. Sperber, 2004, 2004 Symposium on Computational Intelligence in Bioinformatics and Computational Biology.

Multitask Learning Using Regularized Multiple Kernel Learning

Samuel Kaski, Melih Kandemir, Mehmet Gönen, 2011, ICONIP.

Dimensionality Reduction for Data Visualization [Applications Corner]

Samuel Kaski, Jaakko Peltonen, Samuel Kaski, 2011, IEEE Signal Processing Magazine.

Developing a Symbiotic System for Scientific Information Seeking: The MindSee Project

Samuel Kaski, Benjamin Blankertz, Manuel J. A. Eugster, 2015, Symbiotic.

Inverse Modeling of Complex Interactive Behavior with ABC pdf

Jukka Corander, Samuel Kaski, Antti Oulasvirta, 2016, ArXiv.

Self organization of a massive document collection

Samuel Kaski, Teuvo Kohonen, Jarkko Salojärvi, 2000, IEEE Trans. Neural Networks Learn. Syst..

Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space pdf

Samuel Kaski, Sohan Seth, Ritabrata Dutta, 2013, ArXiv.

Self-Organizing Maps of Document Collections

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996 .

Genome-wide association studies with high-dimensional phenotypes

Jukka Corander, Samuel Kaski, Jussi Gillberg, 2012, Statistical applications in genetics and molecular biology.

Directing exploratory search: reinforcement learning from user interactions with keywords

Dorota Glowacka, Samuel Kaski, Tuukka Ruotsalo, 2013, IUI '13.

Local multidimensional scaling

Jarkko Venna, Samuel Kaski, Samuel Kaski, 2006, Neural Networks.

Classification of weak multi-view signals by sharing factors in a mixture of Bayesian group factor analyzers

Samuel Kaski, Tommi Mononen, Sami Remes, 2015, 1512.05610.

Websom for Textual Data Mining

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1999, Artificial Intelligence Review.

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals

Samuel Kaski, Melih Kandemir, Arto Klami, 2015, NeuroImage.

Spike-Timing-Dependent Plasticity

Risto Miikkulainen, Scott Sanner, Kristian Kersting, 2010, Encyclopedia of Machine Learning.

Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation pdf

Samuel Kaski, Makoto Yamada, Song Liu, 2017, ArXiv.

Visualizations for assessing convergence and mixing of Markov chain Monte Carlo simulations

Jarkko Venna, Samuel Kaski, Jaakko Peltonen, 2009, Comput. Stat. Data Anal..

Self-Organizing Maps of Document Collections: A New Approach to Interactive Exploration

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996, KDD.

Learning structures of Bayesian networks for variable groups

Samuel Kaski, Pekka Parviainen, Samuel Kaski, 2015, Int. J. Approx. Reason..

Coloring that Reveals Cluster Structures in Multidimensional Data

Jarkko Venna, Samuel Kaski, Samuel Kaski, 2000 .

Analysis of Gene Expression Data Using Semi-Supervised Clustering

Samuel Kaski, Janne Sinkkonen, Petri Törönen, 2001 .

Sparse Network Lasso for Local High-dimensional Regression pdf

Koh Takeuchi, Tomoharu Iwata, John Shawe-Taylor, 2016, ArXiv.

Bibliography of Self-Organizing Map (SOM) Papers: 1981-1997

Samuel Kaski, Teuvo Kohonen, Jari Kangas, 1998 .

Trustworthiness and metrics in visualizing similarity of gene expression

Jarkko Venna, Samuel Kaski, Petri Törönen, 2003, BMC Bioinformatics.

Scalable Optimization of Neighbor Embedding for Visualization

Samuel Kaski, Jaakko Peltonen, Zhirong Yang, 2013, ICML.

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression

Matti Pirinen, Samuel Kaski, Jussi Gillberg, 2014, Bioinform..

Deep convolutional Gaussian processes pdf

Samuel Kaski, Markus Heinonen, Kenneth Blomqvist, 2018, ECML/PKDD.

Two-Way Grouping by One-Way Topic Models

Samuel Kaski, Kai Puolamäki, Eerika Savia, 2009, IDA.

Self-organizing map-based discovery and visualization of human endogenous retroviral sequence groups

Samuel Kaski, Merja Oja, Göran O. Sperber, 2005, Int. J. Neural Syst..

Searching for functional gene modules with interaction component models

Samuel Kaski, Juuso A. Parkkinen, Samuel Kaski, 2010, BMC Systems Biology.

Monitoring EEG Signal with the Self-Organizing Map

Samuel Kaski, Sirkka-Liisa Joutsiniemi, 1993 .

Unsupervised Inference of Auditory Attention from Biosensors

Samuel Kaski, Melih Kandemir, Arto Klami, 2012, ECML/PKDD.

Bayesian Networks for Variable Groups pdf

Samuel Kaski, Pekka Parviainen, Samuel Kaski, 2015, Probabilistic Graphical Models.

ICML The 28th International Conference on Machine Learning (ICML-11) ICML

Samuel Kaski, Arto Klami, Seppo Virtanen, 2011 .

Combining eye movements and collaborative filtering for proactive information retrieval

Samuel Kaski, Kai Puolamäki, Jarkko Salojärvi, 2005, SIGIR '05.

Proceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010)

Erkki Oja, Antti Honkela, Samuel Kaski, 2010 .

Artificial Neural Networks and Machine Learning Research - ICANN 2011, Part II

Timo Honkela, Samuel Kaski, Mark Girolami, 2011 .

Improving Controllability and Predictability of Interactive Recommendation Interfaces for Exploratory Search

Dorota Glowacka, Samuel Kaski, Antti Kangasrääsiö, 2015, IUI.

Learning Metrics for Visualizing Gene Functional Similarities

Samuel Kaski, Merja Oja, Petri Törönen, 2002 .

Expectation maximization algorithms for conditional likelihoods

Samuel Kaski, Kai Puolamäki, Jarkko Salojärvi, 2005, ICML '05.

Learning to learn implicit queries from gaze patterns

Samuel Kaski, Kai Puolamäki, Antti Ajanki, 2008, ICML '08.

Learning Metrics for SOM-Based Clustering and Visualization of Yeast Gene Expression Data

Samuel Kaski, Petri Törönen, Janne Nikkilä, 2002 .

Using phoneme group specific LVQ-codebooks with HMMs

Samuel Kaski, Kari Torkkola, Pekka Utela, 1992, ICSLP.

Bayesian metabolic flux analysis reveals intracellular flux couplings

Juho Rousu, Samuel Kaski, Janne Wallenius, 2018, Bioinform..

Ninth International Conference on Artificial Neural Networks (ICANN'99), Edinburgh, U.K., September 7-10, 1999

Samuel Kaski, Samuel Kaski, 1999 .

Computationally Efficient Approximation of a Probabilistic Model for Document Representation in the WEBSOM Full-Text Analysis Method

Samuel Kaski, Samuel Kaski, 1997 .

Principle of Learning Metrics for Exploratory Data Analysis

Samuel Kaski, Janne Sinkkonen, Samuel Kaski, 2004, J. VLSI Signal Process..

Functional elements and networks in fMRI

Samuel Kaski, Jarkko Ylipaavalniemi, Ricardo Vigário, 2007, ESANN.

Likelihood-Free Inference by Ratio Estimation

Jukka Corander, Owen Thomas, Samuel Kaski, 2016, Bayesian Analysis.

BCI for Physiological Text Annotation

Samuel Kaski, Manuel J. A. Eugster, Tuukka Ruotsalo, 2017, BCIforReal '17.

Discriminative components of data

Samuel Kaski, Jaakko Peltonen, 2005, IEEE Transactions on Neural Networks.

Approximate Bayesian Computation via Population Monte Carlo and Classification pdf

Samuel Kaski, Henri Pesonen, Charlie Rogers-Smith, 2018, ArXiv.

SOM-Based Exploratory Analysis of Gene Expression Data

Samuel Kaski, Samuel Kaski, 2001, WSOM.

Can relevance of images be inferred from eye movements?

Samuel Kaski, Arto Klami, Craig Saunders, 2008, MIR '08.

Self-Organizing Maps of Very Large Document Collections: Justification for the WEBSOM Method

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1998 .

ICANN The 21st International Conference on Artificial Neural Networks (ICANN) ICANN, Part I

Samuel Kaski, Ilkka Huopaniemi, Tommi Suvitaival, 2011 .

Neurocomputing, Special Issue on Machine Learning for Signal Processing 2010, 80:1-128

Tapani Raiko, Samuel Kaski, Jaakko Peltonen, 2012 .

Integrative and Personalized QSAR Analysis in Cancer by Kernelized Bayesian Matrix Factorization

Krister Wennerberg, Samuel Kaski, Elisabeth Georgii, 2014, J. Chem. Inf. Model..

Inferring Vertex Properties from Topology in Large Networks

Samuel Kaski, Janne Sinkkonen, Janne Aukia, 2007, MLG.

On the identifiability of transmission dynamic models for infectious diseases

Jukka Corander, Samuel Kaski, Michael U. Gutmann, 2015 .

2006 IEEE International Workshop on Machine Learning for Signal Processing, Maynooth, Ireland, Sept. 6-8, 2006

Samuel Kaski, Arto Klami, Samuel Kaski, 2006 .

Proceedings of Workshop 4 of the 10th International Conference on User Modeling; Machine Learning for User Modeling: Challenges, Edinburgh, Scotland, July 24-25, 2005

Samuel Kaski, Ilpo Kojo, Petri Myllymäki, 2005 .

The Adaptive-Subspace Self-Organizing Map (ASSOM)

Samuel Kaski, Teuvo Kohonen, Jarkko Salojärvi, 1997 .

ACM CHI Conference on Human Factors in Computing Systems, CHI 2014, 26 April-1 May, Toronto, Canada

Dorota Glowacka, Samuel Kaski, Jaakko Peltonen, 2014 .

Focused multi-task learning in a Gaussian process framework

Samuel Kaski, Jaakko Peltonen, Gayle Leen, 2012, Machine Learning.

Visualizing gene interaction graphs with local multidimensional scaling

Jarkko Venna, Samuel Kaski, Samuel Kaski, 2006, ESANN.

Local dimension reduction of summary statistics for likelihood-free inference

Samuel Kaski, Jukka Sir'en, Samuel Kaski, 2019, Statistics and Computing.

Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets

Samuel Kaski, Giulio Jacucci, Tomi Peltola, 2016, IUI.

Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study

Jarkko Venna, Samuel Kaski, Samuel Kaski, 2001, ICANN.

Joint Workshop on Personalised Information Access - PIA 2014

Séamus Lawless, Peter Brusilovsky, Samuel Kaski, 2014 .

Characterizing unknown events in MEG data with group factor analysis

Samuel Kaski, Arto Klami, Sami Remes, 2013 .

Inverse reinforcement learning from summary data

Samuel Kaski, Antti Kangasrääsiö, Samuel Kaski, 2017, Machine Learning.

Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations

Samuel Kaski, Simon Rogers, Tommi Suvitaival, 2014, Bioinform..

Methods for Exploratory Cluster Analysis

Samuel Kaski, Teuvo Kohonen, Janne Nikkilä, 2003, Intelligent Exploration of the Web.

Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction

Samuel Kaski, Homayun Afrabandpey, Tomi Peltola, 2016, UMAP.

Probabilistic retrieval and visualization of biologically relevant microarray experiments

Samuel Kaski, Ali Faisal, Alvis Brazma, 2009, BMC Bioinformatics.

Methods for estimating human endogenous retrovirus activities from EST databases

Samuel Kaski, Jaakko Peltonen, Merja Oja, 2007, BMC Bioinformatics.

Learning metrics for self-organizing maps

Samuel Kaski, Jaakko Peltonen, Janne Sinkkonen, 2001, IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222).

International Conference on Artificial Neural Networks (ICANN96), Bochum, Germany, July 16-19, 1996

Timo Honkela, Samuel Kaski, Teuvo Kohonen, 1996 .

Simple integrative preprocessing preserves what is shared in data sources

Samuel Kaski, Arto Klami, Abhishek Tripathi, 2008, BMC Bioinformatics.

Modelling G×E with historical weather information improves genomic prediction in new environments

Samuel Kaski, Jussi Gillberg, Hiroshi Mamitsuka, 2017, bioRxiv.

Optimization Equivalence of Divergences Improves Neighbor Embedding

Samuel Kaski, Jaakko Peltonen, Zhirong Yang, 2014, ICML.

The self-organizing map as a visual neighbor retrieval method

Jarkko Venna, Samuel Kaski, Kristian Nybo, 2007 .

The system should let users incrementally direct their search toward relevant, though not initially obvious, information.

Samuel Kaski, Tuukka Ruotsalo, Giulio Jacucci, 2015 .

Relevance Feedback from Eye Movements for Proactive Information Retrieval

Samuel Kaski, Kai Puolamäki, Jarkko Salojärvi, 2004 .

ELFI: Engine for Likelihood Free Inference

Aki Vehtari, Jukka Corander, Samuel Kaski, 2016, J. Mach. Learn. Res..

Can eyes reveal interest? Implicit queries from gaze patterns

John Shawe-Taylor, Samuel Kaski, Kai Puolamäki, 2009, User Modeling and User-Adapted Interaction.

Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma

Samuel Kaski, Ali Faisal, Eeva Kettunen, 2011, Bioinform..

Intentradar: search user interface that anticipates user's search intents

Dorota Glowacka, Samuel Kaski, Jaakko Peltonen, 2014, CHI Extended Abstracts.

Scalable Bayesian Non-linear Matrix Completion pdf

Samuel Kaski, Paul Blomstedt, Xiangju Qin, 2019, IJCAI.

Three Paths to Relevance

Samuel Kaski, 2010, Brain-Inspired Information Technology.

EntityBot: Supporting Everyday Digital Tasks with Entity Recommendations

Samuel Kaski, Mats Sjöberg, Tuukka Ruotsalo, 2021, RecSys.

Entity Recommendation for Everyday Digital Tasks

Samuel Kaski, Tuukka Ruotsalo, Giulio Jacucci, 2021, ACM Trans. Comput. Hum. Interact..

De-randomizing MCMC dynamics with the diffusion Stein operator pdf

Samuel Kaski, Markus Heinonen, Zheyang Shen, 2021, NeurIPS.

Non-separable Spatio-temporal Graph Kernels via SPDEs pdf

Arno Solin, Samuel Kaski, S. T. John, 2021, ArXiv.

DIVERSE: Bayesian Data IntegratiVE Learning for Precise Drug ResponSE Prediction

Samuel Kaski, Hiroshi Mamitsuka, Betul Guvencpaltun, 2021, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

Locally Differentially Private Bayesian Inference pdf

Antti Honkela, Samuel Kaski, Joonas Jälkö, 2021, ArXiv.

Likelihood-Free Inference by Ratio Estimation

Jukka Corander, Samuel Kaski, Michael U. Gutmann, 2016, Bayesian Analysis.

Likelihood-Free Inference in State-Space Models pdf

Samuel Kaski, Andrew Howes, Alexander Aushev, 2021 .

Prior Knowledge Elicitation: The Past, Present, and Future

Aki Vehtari, Jukka Corander, Samuel Kaski, 2021, Bayesian Analysis.

Stochastic cluster embedding pdf

Jukka Corander, Samuel Kaski, Denis Sedov, 2021, Statistics and Computing.

Dimensionality Reduction for Data Visualization

Samuel Kaski, Jaakko Peltonen, 2010 .

Acta Polytechnica Scandinavica Mathematics, Computing and Management in Engineering Series No. 82 Data Exploration Using Self-organizing Maps Data Exploration Using Self-organizing Maps. Acta Polytechnica

Samuel Kaski, Samuel Kaski, 1997 .

5th Workshop on Self-Organizing Maps : Paris 1 Panthéon-Sorbonne University 5th-8th September 2005 : proceedings

Barbara Hammer, Samuel Kaski, Teuvo Kohonen, 2005 .

Exploration and retrieval of whole-metagenome sequencing

Antti Honkela, Samuel Kaski, Sohan Seth, 2014 .

Chapter 10 Self-organization of very large document collections

Samuel Kaski, Teuvo Kohonen, Jarkko Salojärvi, .

Regression Analysis in Small-n-Large-p Using Interactive Prior Elicitation of Pairwise Similarities

Samuel Kaski, Homayun Afrabandpey, Tomi Peltola, 2016 .

Toward the Replacement of Animal Experiments through the Bioinformatics-driven Analysis of ‘Omics’ Data from Human Cell Cultures

Ola Spjuth, Samuel Kaski, Egon Willighagen, 2015, Alternatives to laboratory animals : ATLA.

Can Relevance be Inferred from Eye Movements in Information Retrieval

Samuel Kaski, Jarkko Salojärvi, Samuel Kaski, 2003 .

Modeling of relevance

Jarkko Venna, Samuel Kaski, Kai Puolamäki, 2008 .

A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury

Krister Wennerberg, Samuel Kaski, Pekka Kohonen, 2017, Nature Communications.

On the Identifiability of Transmission Dynamic Models for Infectious Diseases

Jukka Corander, Samuel Kaski, Jarno Lintusaari, 2015, Genetics.

Clustering of Human Endogenous Retrovirus Sequences with Median Self-Organizing Map

Samuel Kaski, Panu Somervuo, Teuvo Kohonen, 2003 .

Structures of Welfare and Poverty in the World Discovered by the Self-Organizing Map

Samuel Kaski, Teuvo Kohonen, T. Kohonen, 1995 .

Predicting relevance of parts of an image

Kitsuchart Pasupa, Gabriela Csurka, Samuel Kaski, 2009 .

Principle of Learning Metrics for Data Analysis

Samuel Kaski, Janne Sinkkonen, Samuel Kaski, 2004 .

A simple infinite topic mixture for rich graphs and relational data

Samuel Kaski, Janne Sinkkonen, Janne Aukia, 2008 .

From learning metrics towards dependency exploration

Samuel Kaski, 2005 .

PRIMA — Proactive information retrieval by adaptive models of users ’ attention and interests

Samuel Kaski, Kai Puolamäki, Jarkko Salojärvi, 2004 .

Gene expression profiles in asbestos-exposed epithelial and mesothelial lung cell lines

Samuel Kaski, Jaakko Hollmén, Leo Lahti, 2007, BMC Genomics.

Local Multidimensional Scaling with Controlled Tradeoff Between Trustworthiness and Continuity

Jarkko Venna, Samuel Kaski, Samuel Kaski, 2005 .

Learning Metri s for Self-Organizing Maps

Samuel Kaski, Jaakko Peltonen, Janne Sinkkonen, 2001 .

High Density Lipoprotein Structural Changes and Drug Response in Lipidomic Profiles following the Long-Term Fenofibrate Therapy in the FIELD Substudy

Samuel Kaski, Ilkka Huopaniemi, Laxman Yetukuri, 2011, PloS one.

Exploring the independence of gene regulatory modules

Antti Honkela, Samuel Kaski, Janne Nikkilä, 2006 .

Phenotype-driven identification of epithelial signalling clusters

Samuel Kaski, Tomi Peltola, Juha Klefström, 2018, Scientific Reports.