Using phoneme group specific LVQ-codebooks with HMMs. - Pekka Utela; Samuel Kaski; Kari Torkkola (ICSLP, 1992)

Winner-take-all networks for physiological models of competitive learning. - Samuel Kaski; Teuvo Kohonen (Neural Networks, 1994)

Self-organizing map in recognition of topographic patterns of EEG spectra. - Sirkka-Liisa Joutsiniemi; Samuel Kaski; T. Andreo Larsen (IEEE Trans. Biomed. Eng., 1995)

Comparing Self-Organizing Maps. - Samuel Kaski; Krista Lagus (ICANN, 1996)

Very Large Two-Level SOM for the Browsing of Newsgroups. - Teuvo Kohonen; Samuel Kaski; Krista Lagus; Timo Honkela (ICANN, 1996)

Compression of vector quantization code sequences based on code frequencies and spatial redundancies. - Jari Kangas 001; Samuel Kaski (ICIP (3), 1996)

Exploration of full-text databases with self-organizing maps. - Timo Honkela; Samuel Kaski; Krista Lagus; Teuvo Kohonen (ICNN, 1996)

Self-Organizing Maps of Document Collections: A New Approach to Interactive Exploration. - Krista Lagus; Timo Honkela; Samuel Kaski; Teuvo Kohonen (KDD, 1996)

Self-organized Formation of Various Invariant-feature Filters in the Adaptive-subspace SOM. - Teuvo Kohonen; Samuel Kaski; Harri Lappalainen (Neural Comput., 1997)

Computationally Efficient Approximation of a Probabilistic Model for Document Representation in the WEBSOM Full-Text Analysis Method. - Samuel Kaski (Neural Process. Lett., 1997)

Methods for interpreting a self-organized map in data analysis. - Samuel Kaski; Janne Nikkilä; Teuvo Kohonen (ESANN, 1998)

WEBSOM - Self-organizing maps of document collections. - Samuel Kaski; Timo Honkela; Krista Lagus; Teuvo Kohonen (Neurocomputing, 1998)

Websom for Textual Data Mining. - Krista Lagus; Timo Honkela; Samuel Kaski; Teuvo Kohonen (Artif. Intell. Rev., 1999)

Clustering by Similarity in an Auxiliary Space. - Janne Sinkkonen; Samuel Kaski (IDEAL, 2000)

Metrics that Learn Relevance. - Samuel Kaski; Janne Sinkkonen (IJCNN (5), 2000)

Self organization of a massive document collection. - Teuvo Kohonen; Samuel Kaski; Krista Lagus; Jarkko Salojärvi; Jukka Honkela; Vesa Paatero; Antti Saarela (IEEE Trans. Neural Networks Learn. Syst., 2000)

Data Visualization and Analysis with Self-Organizing Maps in Learning Metrics. - Samuel Kaski; Janne Sinkkonen; Jaakko Peltonen (DaWaK, 2001)

Clustering Gene Expression Data by Mutual Information with Gene Function. - Samuel Kaski; Janne Sinkkonen; Janne Nikkilä (ICANN, 2001)

Neighborhood Preservation in Nonlinear Projection Methods: An Experimental Study. - Jarkko Venna; Samuel Kaski (ICANN, 2001)

SOM-Based Exploratory Analysis of Gene Expression Data. - Samuel Kaski (WSOM, 2001)

A Topography-Preserving Latent Variable Model with Learning Metrics. - Samuel Kaski; Janne Sinkkonen (WSOM, 2001)

Bankruptcy analysis with self-organizing maps in learning metrics. - Samuel Kaski; Janne Sinkkonen; Jaakko Peltonen (IEEE Trans. Neural Networks, 2001)

Discriminative Clustering: Optimal Contingency Tables by Learning Metrics. - Janne Sinkkonen; Samuel Kaski; Janne Nikkilä (ECML, 2002)

Learning More Accurate Metrics for Self-Organizing Maps. - Jaakko Peltonen; Arto Klami; Samuel Kaski (ICANN, 2002)

Electronic editor: automatic content-based sequential compilation of newspaper articles. - Ville Ollikainen; Christer Bäckström; Samuel Kaski (Neurocomputing, 2002)

Clustering Based on Conditional Distributions in an Auxiliary Space. - Janne Sinkkonen; Samuel Kaski (Neural Comput., 2002)

Analysis and visualization of gene expression data using Self-Organizing Maps. - Janne Nikkilä; Petri Törönen; Samuel Kaski; Jarkko Venna; Eero Castrén; Garry Wong (Neural Networks, 2002)

Visualizations for Assessing Convergence and Mixing of MCMC. - Jarkko Venna; Samuel Kaski; Jaakko Peltonen (ECML, 2003)

Informative Discriminant Analysis. - Samuel Kaski; Jaakko Peltonen (ICML, 2003)

Regularized discriminative clustering. - Samuel Kaski; Janne Sinkkonen; Arto Klami (NNSP, 2003)

Trustworthiness and metrics in visualizing similarity of gene expression. - Samuel Kaski; Janne Nikkilä; Merja Oja; Jarkko Venna; Petri Törönen; Eero Castrén (BMC Bioinform., 2003)

Methods for Exploratory Cluster Analysis. - Samuel Kaski; Janne Nikkilä; Teuvo Kohonen (Intelligent Exploration of the Web, 2003)

Grouping and visualizing human endogenous retroviruses by bootstrapping median self-organizing maps. - Merja Oja; Göran O. Sperber; Jonas Blomberg; Samuel Kaski (CIBCB, 2004)

Associative Clustering. - Janne Sinkkonen; Janne Nikkilä; Leo Lahti; Samuel Kaski (ECML, 2004)

Sequential information bottleneck for finite data. - Jaakko Peltonen; Janne Sinkkonen; Samuel Kaski (ICML, 2004)

Exploring Dependencies Between Yeast Stress Genes and Their Regulators. - Janne Nikkilä; Christophe Roos; Samuel Kaski (IDEAL, 2004)

On text-based estimation of document relevance. - Eerika Savia; Samuel Kaski; Ville H. Tuulos; Petri Myllymäki (IJCNN, 2004)

Mining massive document collections by the WEBSOM method. - Krista Lagus; Samuel Kaski; Teuvo Kohonen (Inf. Sci., 2004)

Improved learning of Riemannian metrics for exploratory analysis. - Jaakko Peltonen; Arto Klami; Samuel Kaski (Neural Networks, 2004)

Principle of Learning Metrics for Exploratory Data Analysis. - Samuel Kaski; Janne Sinkkonen (J. VLSI Signal Process., 2004)

On Discriminative Joint Density Modeling. - Jarkko Salojärvi; Kai Puolamäki; Samuel Kaski (ECML, 2005)

Implicit Relevance Feedback from Eye Movements. - Jarkko Salojärvi; Kai Puolamäki; Samuel Kaski (ICANN (1), 2005)

Non-parametric dependent components. - Arto Klami; Samuel Kaski (ICASSP (5), 2005)

Expectation maximization algorithms for conditional likelihoods. - Jarkko Salojärvi; Kai Puolamäki; Samuel Kaski (ICML, 2005)

Combining eye movements and collaborative filtering for proactive information retrieval. - Kai Puolamäki; Jarkko Salojärvi; Eerika Savia; Jaana Simola; Samuel Kaski (SIGIR, 2005)

Two-Way Latent Grouping Model for User Preference Prediction. - Eerika Savia; Kai Puolamäki; Janne Sinkkonen; Samuel Kaski (UAI, 2005)

Exploratory modeling of yeast stress response and its regulation with gcca and associative clustering. - Janne Nikkilä; Christophe Roos; Eerika Savia; Samuel Kaski (Int. J. Neural Syst., 2005)

Self-organizing map-based discovery and visualization of human endogenous retroviral sequence groups. - Merja Oja; Göran O. Sperber; Jonas Blomberg; Samuel Kaski (Int. J. Neural Syst., 2005)

Discriminative clustering. - Samuel Kaski; Janne Sinkkonen; Arto Klami (Neurocomputing, 2005)

Associative Clustering for Exploring Dependencies between Functional Genomics Data Sets. - Samuel Kaski; Janne Nikkilä; Janne Sinkkonen; Leo Lahti; Juha E. A. Knuuttila; Christophe Roos (IEEE ACM Trans. Comput. Biol. Bioinform., 2005)

Discriminative components of data. - Jaakko Peltonen; Samuel Kaski (IEEE Trans. Neural Networks, 2005)

Neural networks and machine learning in bioinformatics - theory and applications. - Udo Seiffert; Barbara Hammer; Samuel Kaski; Thomas Villmann (ESANN, 2006)

Visualizing gene interaction graphs with local multidimensional scaling. - Jarkko Venna; Samuel Kaski (ESANN, 2006)

Local multidimensional scaling. - Jarkko Venna; Samuel Kaski (Neural Networks, 2006)

Learning from Relevant Tasks Only. - Samuel Kaski; Jaakko Peltonen (ECML, 2007)

Functional elements and networks in fMRI. - Jarkko Ylipaavalniemi; Eerika Savia; Ricardo Vigário; Samuel Kaski (ESANN, 2007)

Local dependent components. - Arto Klami; Samuel Kaski (ICML, 2007)

Inferring Vertex Properties from Topology in Large Networks. - Janne Sinkkonen; Janne Aukia; Samuel Kaski (MLG, 2007)

Probabilistic modeling and machine learning in structural and systems biology. - Samuel Kaski; Juho Rousu; Esko Ukkonen (BMC Bioinform., 2007)

Methods for estimating human endogenous retrovirus activities from EST databases. - Merja Oja; Jaakko Peltonen; Jonas Blomberg; Samuel Kaski (BMC Bioinform., 2007)

Comparison of visualization methods for an atlas of gene expression data sets. - Jarkko Venna; Samuel Kaski (Inf. Vis., 2007)

Information Retrieval by Inferring Implicit Queries from Eye Movements. - David R. Hardoon; John Shawe-Taylor; Antti Ajanki; Kai Puolamäki; Samuel Kaski (AISTATS, 2007)

Nonlinear Dimensionality Reduction as Information Retrieval. - Jarkko Venna; Samuel Kaski (AISTATS, 2007)

Learning to learn implicit queries from gaze patterns. - Kai Puolamäki; Antti Ajanki; Samuel Kaski (ICML, 2008)

An Analysis of Generalization Error in Relevant Subtask Learning. - Keisuke Yamazaki; Samuel Kaski (ICONIP (1), 2008)

Can relevance of images be inferred from eye movements? - Arto Klami; Craig Saunders; Teófilo Emídio de Campos; Samuel Kaski (Multimedia Information Retrieval, 2008)

Infinite mixtures for multi-relational categorical data. - Janne Sinkkonen; Janne Aukia; Samuel Kaski (MLG@ICML, 2008)

Simple integrative preprocessing preserves what is shared in data sources. - Abhishek Tripathi; Arto Klami; Samuel Kaski (BMC Bioinform., 2008)

Probabilistic approach to detecting dependencies between data sets. - Arto Klami; Samuel Kaski (Neurocomputing, 2008)

Automatic Choice of Control Measurements. - Gayle Leen; David R. Hardoon; Samuel Kaski (ACML, 2009)

Supervised nonlinear dimensionality reduction by Neighbor Retrieval. - Jaakko Peltonen; Helena Aidos; Samuel Kaski (ICASSP, 2009)

Fast dependent components for fMRI analysis. - Eerika Savia; Arto Klami; Samuel Kaski (ICASSP, 2009)

Using dependencies to pair samples for multi-view learning. - Abhishek Tripathi; Arto Klami; Samuel Kaski (ICASSP, 2009)

Learning to rank images from eye movements. - Kitsuchart Pasupa; Craig Saunders; Sándor Szedmák; Arto Klami; Samuel Kaski; Steve R. Gunn (ICCV Workshops, 2009)

GaZIR: gaze-based zooming interface for image retrieval. - László Kozma 002; Arto Klami; Samuel Kaski (ICMI, 2009)

Bayesian Solutions to the Label Switching Problem. - Kai Puolamäki; Samuel Kaski (IDA, 2009)

Two-Way Grouping by One-Way Topic Models. - Eerika Savia; Kai Puolamäki; Samuel Kaski (IDA, 2009)

A Block Model Suitable for Sparse Graphs. - Juuso A. Parkkinen; Janne Sinkkonen; Ádám Gyenge; Samuel Kaski (MLG/SRL@ILP, 2009)

Probabilistic retrieval and visualization of biologically relevant microarray experiments. - José Caldas; Nils Gehlenborg; Ali Faisal; Alvis Brazma; Samuel Kaski (BMC Bioinform., 2009)

Visualizations for assessing convergence and mixing of Markov chain Monte Carlo simulations. - Jaakko Peltonen; Jarkko Venna; Samuel Kaski (Comput. Stat. Data Anal., 2009)

Two-way analysis of high-dimensional collinear data. - Ilkka Huopaniemi; Tommi Suvitaival; Janne Nikkilä; Matej Oresic; Samuel Kaski (Data Min. Knowl. Discov., 2009)

Latent grouping models for user preference prediction. - Eerika Savia; Kai Puolamäki; Samuel Kaski (Mach. Learn., 2009)

Dependencies between stimuli and spatially independent fMRI sources: Towards brain correlates of natural stimuli. - Jarkko Ylipaavalniemi; Eerika Savia; Sanna Malinen; Riitta Hari; Ricardo Vigário; Samuel Kaski (NeuroImage, 2009)

Can eyes reveal interest? Implicit queries from gaze patterns. - Antti Ajanki; David R. Hardoon; Samuel Kaski; Kai Puolamäki; John Shawe-Taylor (User Model. User Adapt. Interact., 2009)

Inferring object relevance from gaze in dynamic scenes. - Melih Kandemir; Veli-Matti Saarinen; Samuel Kaski (ETRA, 2010)

An information retrieval perspective on visualization of gene expression data with ontological annotation. - Jaakko Peltonen; Helena Aidos; Nils Gehlenborg; Alvis Brazma; Samuel Kaski (ICASSP, 2010)

Graph visualization with latent variable models. - Juuso A. Parkkinen; Kristian Nybo; Jaakko Peltonen; Samuel Kaski (MLG@KDD, 2010)

Graphical Multi-way Models. - Ilkka Huopaniemi; Tommi Suvitaival; Matej Oresic; Samuel Kaski (ECML/PKDD (1), 2010)

Variational Bayesian Mixture of Robust CCA Models. - Jaakko Viinikanoja; Arto Klami; Samuel Kaski (ECML/PKDD (3), 2010)

Bayesian exponential family projections for coupled data sources. - Arto Klami; Seppo Virtanen; Samuel Kaski (UAI, 2010)

Multivariate multi-way analysis of multi-source data. - Ilkka Huopaniemi; Tommi Suvitaival; Janne Nikkilä; Matej Oresic; Samuel Kaski (Bioinform., 2010)

Global modeling of transcriptional responses in interaction networks. - Leo Lahti; Juha E. A. Knuuttila; Samuel Kaski (Bioinform., 2010)

Searching for functional gene modules with interaction component models. - Juuso A. Parkkinen; Samuel Kaski (BMC Syst. Biol., 2010)

Relevant subtask learning by constrained mixture models. - Jaakko Peltonen; Yusuf Yaslan; Samuel Kaski (Intell. Data Anal., 2010)

Pinview: Implicit Feedback in Content-Based Image Retrieval. - Peter Auer; Zakria Hussain; Samuel Kaski; Arto Klami; Jussi Kujala; Jorma Laaksonen; Alex Po Leung; Kitsuchart Pasupa; John Shawe-Taylor (WAPA, 2010)

Information Retrieval Perspective to Nonlinear Dimensionality Reduction for Data Visualization. - Jarkko Venna; Jaakko Peltonen; Kristian Nybo; Helena Aidos; Samuel Kaski (J. Mach. Learn. Res., 2010)

Infinite factorization of multiple non-parametric views. - Simon Rogers; Arto Klami; Janne Sinkkonen; Mark A. Girolami; Samuel Kaski (Mach. Learn., 2010)

Self-Organizing Maps. - Samuel Kaski (Encyclopedia of Machine Learning, 2010)

Three Paths to Relevance. - Samuel Kaski (Brain-Inspired Information Technology, 2010)

Probabilistic Proactive Timeline Browser. - Antti Ajanki; Samuel Kaski (ICANN (2), 2011)

Cross-Species Translation of Multi-way Biomarkers. - Tommi Suvitaival; Ilkka Huopaniemi; Matej Oresic; Samuel Kaski (ICANN (1), 2011)

Bayesian CCA via Group Sparsity. - Seppo Virtanen; Arto Klami; Samuel Kaski (ICML, 2011)

Multitask Learning Using Regularized Multiple Kernel Learning. - Mehmet Gönen; Melih Kandemir; Samuel Kaski (ICONIP (2), 2011)

Focused Multi-task Learning Using Gaussian Processes. - Gayle Leen; Jaakko Peltonen; Samuel Kaski (ECML/PKDD (2), 2011)

Matching samples of multiple views. - Abhishek Tripathi; Arto Klami; Matej Oresic; Samuel Kaski (Data Min. Knowl. Discov., 2011)

Hierarchical Generative Biclustering for MicroRNA Expression Analysis. - José Caldas; Samuel Kaski (J. Comput. Biol., 2011)

Generative Modeling for Maximizing Precision and Recall in Information Visualization. - Jaakko Peltonen; Samuel Kaski (AISTATS, 2011)

Introduction to the special issue on mining and learning with graphs. - S. V. N. Vishwanathan; Samuel Kaski; Jennifer Neville; Stefan Wrobel (Mach. Learn., 2011)

Metabolic Regulation in Progression to Autoimmune Diabetes. - Marko Sysi-Aho; Andrey Ermolov; Peddinti V. Gopalacharyulu; Abhishek Tripathi; Tuulikki Seppänen-Laakso; Johanna Maukonen; Ismo Mattila; Suvi T. Ruohonen; Laura Vähätalo; Laxman Yetukuri; Taina Härkönen; Erno Lindfors; et al. (PLoS Comput. Biol., 2011)

Dimensionality Reduction for Data Visualization [Applications Corner]. - Samuel Kaski; Jaakko Peltonen (IEEE Signal Process. Mag., 2011)

Probabilistic Analysis of Probe Reliability in Differential Gene Expression Studies with Short Oligonucleotide Arrays. - Leo Lahti; Laura Elo; Tero Aittokallio; Samuel Kaski (IEEE ACM Trans. Comput. Biol. Bioinform., 2011)

An augmented reality interface to contextual information. - Antti Ajanki; Mark Billinghurst; Hannes Gamper; Toni Järvenpää; Melih Kandemir; Samuel Kaski; Markus Koskela; Mikko Kurimo; Jorma Laaksonen; Kai Puolamäki; Teemu Ruokolainen; Timo Tossavainen (Virtual Real., 2011)

Sparse Nonparametric Topic Model for Transfer Learning. - Ali Faisal; Jussi Gillberg; Jaakko Peltonen; Gayle Leen; Samuel Kaski (ESANN, 2012)

Learning relevance from natural eye movements in pervasive interfaces. - Melih Kandemir; Samuel Kaski (ICMI, 2012)

Unsupervised Inference of Auditory Attention from Biosensors. - Melih Kandemir; Arto Klami; Akos Vetek; Samuel Kaski (ECML/PKDD (2), 2012)

Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma. - José Caldas; Nils Gehlenborg; Eeva Kettunen; Ali Faisal; Mikko Rönty; Andrew G. Nicholson; Sakari Knuutila; Alvis Brazma; Samuel Kaski (Bioinform., 2012)

Targeted retrieval of gene expression measurements using regulatory models. - Elisabeth Georgii; Jarkko Salojärvi; Mikael Brosché; Jaakko Kangasjärvi; Samuel Kaski (Bioinform., 2012)

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs. - Suleiman A. Khan; Ali Faisal; John Mpindi; Juuso A. Parkkinen; Tuomo Kalliokoski; Antti Poso; Olli-P. Kallioniemi; Krister Wennerberg; Samuel Kaski (BMC Bioinform., 2012)

Machine learning for signal processing 2010. - Jaakko Peltonen; Tapani Raiko; Samuel Kaski (Neurocomputing, 2012)

Bayesian Group Factor Analysis. - Seppo Virtanen; Arto Klami; Suleiman A. Khan; Samuel Kaski (AISTATS, 2012)

Focused multi-task learning in a Gaussian process framework. - Gayle Leen; Jaakko Peltonen; Samuel Kaski (Mach. Learn., 2012)

Supporting exploratory search tasks with interactive user modeling. - Tuukka Ruotsalo; Kumaripaba Athukorala; Dorota Glowacka; Ksenia Konyushkova; Antti Oulasvirta; Samuli Kaipiainen; Samuel Kaski; Giulio Jacucci (ASIST, 2013)

Directing exploratory search with interactive intent modeling. - Tuukka Ruotsalo; Jaakko Peltonen; Manuel J. A. Eugster; Dorota Glowacka; Ksenia Konyushkova; Kumaripaba Athukorala; Ilkka Kosunen; Aki Reijonen; Petri Myllymäki; Giulio Jacucci; Samuel Kaski (CIKM, 2013)

Adaptive timeline interface to personal history data. - Antti Ajanki; Markus Koskela; Jorma Laaksonen; Samuel Kaski (ICMI, 2013)

Kernelized Bayesian Matrix Factorization. - Mehmet Gönen; Suleiman A. Khan; Samuel Kaski (ICML (3), 2013)

Scalable Optimization of Neighbor Embedding for Visualization. - Zhirong Yang; Jaakko Peltonen; Samuel Kaski (ICML (2), 2013)

Directing exploratory search: reinforcement learning from user interactions with keywords. - Dorota Glowacka; Tuukka Ruotsalo; Ksenia Konyushkova; Kumaripaba Athukorala; Samuel Kaski; Giulio Jacucci (IUI, 2013)

SciNet: a system for browsing scientific literature through keyword manipulation. - Dorota Glowacka; Tuukka Ruotsalo; Ksenia Konyushkova; Kumaripaba Athukorala; Samuel Kaski; Giulio Jacucci (IUI Companion, 2013)

Information Retrieval Perspective to Interactive Data Visualization. - Jaakko Peltonen; Max Sandholm; Samuel Kaski (EuroVis (Short Papers), 2013)

Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space. - Ritabrata Dutta; Sohan Seth; Samuel Kaski (CoRR, 2013)

Bayesian Information Sharing Between Noise And Regression Models Improves Prediction of Weak Effects. - Jussi Gillberg; Pekka Marttinen; Matti Pirinen; Antti J. Kangas; Pasi Soininen; Marjo-Riitta Järvelin; Mika Ala-Korpela; Samuel Kaski (CoRR, 2013)

Bayesian Canonical correlation analysis. - Arto Klami; Seppo Virtanen; Samuel Kaski (J. Mach. Learn. Res., 2013)

Optimal Neighborhood Preserving Visualization by Maximum Satisfiability. - Kerstin Bunte; Matti Järvisalo; Jeremias Berg; Petri Myllymäki; Jaakko Peltonen; Samuel Kaski (AAAI, 2014)

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

Intentradar: search user interface that anticipates user's search intents. - Tuukka Ruotsalo; Jaakko Peltonen; Manuel J. A. Eugster; Dorota Glowacka; Aki Reijonen; Giulio Jacucci; Petri Myllymäki; Samuel Kaski (CHI Extended Abstracts, 2014)

Optimization Equivalence of Divergences Improves Neighbor Embedding. - Zhirong Yang; Jaakko Peltonen; Samuel Kaski (ICML, 2014)

Retrieval of Experiments by Efficient Comparison of Marginal Likelihoods. - Sohan Seth; John Shawe-Taylor; Samuel Kaski (ICONIP (2), 2014)

Bayesian Multi-view Tensor Factorization. - Suleiman A. Khan; Samuel Kaski (ECML/PKDD (1), 2014)

Predicting term-relevance from brain signals. - Manuel J. A. Eugster; Tuukka Ruotsalo; Michiel M. A. Spapé; Ilkka Kosunen; Oswald Barral; Niklas Ravaja; Giulio Jacucci; Samuel Kaski (SIGIR, 2014)

Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis. - Suleiman A. Khan; Seppo Virtanen; Olli-P. Kallioniemi; Krister Wennerberg; Antti Poso; Samuel Kaski (Bioinform., 2014)

Assessing multivariate gene-metabolome associations with rare variants using Bayesian reduced rank regression. - Pekka Marttinen; Matti Pirinen; Antti-Pekka Sarin; Jussi Gillberg; Johannes Kettunen; Ida Surakka; Antti J. Kangas; Pasi Soininen; Paul F. O'Reilly; Marika Kaakinen; Mika Kähönen; Terho Lehtimäki; et al. (Bioinform., 2014)

Exploration and retrieval of whole-metagenome sequencing samples. - Sohan Seth; Niko Välimäki; Samuel Kaski; Antti Honkela (Bioinform., 2014)

Stronger findings for metabolomics through Bayesian modeling of multiple peaks and compound correlations. - Tommi Suvitaival; Simon Rogers; Samuel Kaski (Bioinform., 2014)

Probabilistic drug connectivity mapping. - Juuso A. Parkkinen; Samuel Kaski (BMC Bioinform., 2014)

Stronger findings from mass spectral data through multi-peak modeling. - Tommi Suvitaival; Simon Rogers; Samuel Kaski (BMC Bioinform., 2014)

Retrieval of Experiments by Efficient Estimation of Marginal Likelihood. - Sohan Seth; John Shawe-Taylor; Samuel Kaski (CoRR, 2014)

Multi-task and multi-view learning of user state. - Melih Kandemir; Akos Vetek; Mehmet Gönen; Arto Klami; Samuel Kaski (Neurocomputing, 2014)

Integrative and Personalized QSAR Analysis in Cancer by Kernelized Bayesian Matrix Factorization. - Muhammad Ammad-ud-din; Elisabeth Georgii; Mehmet Gönen; Tuomo Laitinen; Olli-P. Kallioniemi; Krister Wennerberg; Antti Poso; Samuel Kaski (J. Chem. Inf. Model., 2014)

Kernelized Bayesian Matrix Factorization. - Mehmet Gönen; Samuel Kaski (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Majorization-Minimization for Manifold Embedding. - Zhirong Yang; Jaakko Peltonen; Samuel Kaski (AISTATS, 2015)

Exploring Peripheral Physiology as a Predictor of Perceived Relevance in Information Retrieval. - Oswald Barral; Manuel J. A. Eugster; Tuukka Ruotsalo; Michiel M. A. Spapé; Ilkka Kosunen; Niklas Ravaja; Samuel Kaski; Giulio Jacucci (IUI, 2015)

Improving Controllability and Predictability of Interactive Recommendation Interfaces for Exploratory Search. - Antti Kangasrääsiö; Dorota Glowacka; Samuel Kaski (IUI, 2015)

SciNet: Interactive Intent Modeling for Information Discovery. - Tuukka Ruotsalo; Jaakko Peltonen; Manuel J. A. Eugster; Dorota Glowacka; Aki Reijonen; Giulio Jacucci; Petri Myllymäki; Samuel Kaski (SIGIR, 2015)

Developing a Symbiotic System for Scientific Information Seeking: The MindSee Project. - Luciano Gamberini; Anna Spagnolli; Benjamin Blankertz; Samuel Kaski; Jonathan Freeman; Laura Acqualagna; Oswald Barral; Maura Bellio; Luca Chech; Manuel J. A. Eugster; Eva Ferrari; Paolo Negri; et al. (Symbiotic, 2015)

Interactive intent modeling: information discovery beyond search. - Tuukka Ruotsalo; Giulio Jacucci; Petri Myllymäki; Samuel Kaski (Commun. ACM, 2015)

Towards brain-activity-controlled information retrieval: Decoding image relevance from MEG signals. - Jukka-Pekka Kauppi; Melih Kandemir; Veli-Matti Saarinen; Lotta Hirvenkari; Lauri Parkkonen; Arto Klami; Riitta Hari; Samuel Kaski (NeuroImage, 2015)

Group Factor Analysis. - Arto Klami; Seppo Virtanen; Eemeli Leppäaho; Samuel Kaski (IEEE Trans. Neural Networks Learn. Syst., 2015)

Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo. - Markus Heinonen; Henrik Mannerström; Juho Rousu; Samuel Kaski; Harri Lähdesmäki (AISTATS, 2016)

Visualizations relevant to the user by multi-view latent variable factorization. - Seppo Virtanen; Homayun Afrabandpey; Samuel Kaski (ICASSP, 2016)

Regression with n→1 by Expert Knowledge Elicitation. - Marta Soare; Muhammad Ammad-ud-din; Samuel Kaski (ICMLA, 2016)

A Robust Convex Formulation for Ensemble Clustering. - Junning Gao; Makoto Yamada; Samuel Kaski; Hiroshi Mamitsuka; Shanfeng Zhu (IJCAI, 2016)

Preliminary Studies on Personalized Preference Prediction from Gaze in Comparing Visualizations. - Hamed Rezazadegan Tavakoli; Hanieh Poostchi; Jaakko Peltonen; Jorma Laaksonen; Samuel Kaski (ISVC (2), 2016)

Interactive Intent Modeling from Multiple Feedback Domains. - Pedram Daee; Joel Pyykkö; Dorota Glowacka; Samuel Kaski (IUI, 2016)

Dealing with Concept Drift in Exploratory Search: An Interactive Bayesian Approach. - Antti Kangasrääsiö; Yi Chen; Dorota Glowacka; Samuel Kaski (IUI Companion, 2016)

Bayesian Networks for Variable Groups. - Pekka Parviainen; Samuel Kaski (Probabilistic Graphical Models, 2016)

Interactive Modeling of Concept Drift and Errors in Relevance Feedback. - Antti Kangasrääsiö; Yi Chen; Dorota Glowacka; Samuel Kaski (UMAP, 2016)

Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization. - Muhammad Ammad-ud-din; Suleiman A. Khan; Disha Malani; Astrid Murumägi; Olli-P. Kallioniemi; Tero Aittokallio; Samuel Kaski (Bioinform., 2016)

Modelling-based experiment retrieval: a case study with gene expression clustering. - Paul Blomstedt; Ritabrata Dutta; Sohan Seth; Alvis Brazma; Samuel Kaski (Bioinform., 2016)

Sparse group factor analysis for biclustering of multiple data sources. - Kerstin Bunte; Eemeli Leppäaho; Inka Saarinen; Samuel Kaski (Bioinform., 2016)

Interactive Prior Elicitation of Features Similarities for Small Sample Size Prediction. - Homayun Afrabandpey; Tomi Peltola; Samuel Kaski (CoRR, 2016)

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals. - Manuel J. A. Eugster; Tuukka Ruotsalo; Michiel M. A. Spapé; Oswald Barral; Niklas Ravaja; Giulio Jacucci; Samuel Kaski (CoRR, 2016)

Efficient differentially private learning improves drug sensitivity prediction. - Antti Honkela; Mrinal Das; Onur Dikmen; Samuel Kaski (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)

Regression with n$ to$1 by Expert Knowledge Elicitation. - Marta Soare; Muhammad Ammad-ud-din; Samuel Kaski (CoRR, 2016)

Sparse Network Lasso for Local High-dimensional Regression. - Makoto Yamada; Koh Takeuchi 001; Tomoharu Iwata; John Shawe-Taylor; Samuel Kaski (CoRR, 2016)

A Latent Feature Model Approach to Biclustering. - José Caldas; Samuel Kaski (Int. J. Knowl. Discov. Bioinform., 2016)

Multiple Output Regression with Latent Noise. - Jussi Gillberg; Pekka Marttinen; Matti Pirinen; Antti J. Kangas; Pasi Soininen; Mehreen Ali; Aki S. Havulinna; Marjo-Riitta Järvelin; Mika Ala-Korpela; Samuel Kaski (J. Mach. Learn. Res., 2016)

Bayesian multi-tensor factorization. - Suleiman A. Khan; Eemeli Leppäaho; Samuel Kaski (Mach. Learn., 2016)

Extracting relevance and affect information from physiological text annotation. - Oswald Barral; Ilkka Kosunen; Tuukka Ruotsalo; Michiel M. A. Spapé; Manuel J. A. Eugster; Niklas Ravaja; Samuel Kaski; Giulio Jacucci (User Model. User Adapt. Interact., 2016)

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings. - Sami Remes; Markus Heinonen; Samuel Kaski (ACML, 2017)

Localized Lasso for High-Dimensional Regression. - Makoto Yamada; Koh Takeuchi 001; Tomoharu Iwata; John Shawe-Taylor; Samuel Kaski (AISTATS, 2017)

Inferring Cognitive Models from Data using Approximate Bayesian Computation. - Antti Kangasrääsiö; Kumaripaba Athukorala; Andrew Howes 001; Jukka Corander; Samuel Kaski; Antti Oulasvirta (CHI, 2017)

BCI for Physiological Text Annotation. - Oswald Barral; Ilkka Kosunen; Tuukka Ruotsalo; Michiel M. A. Spapé; Manuel J. A. Eugster; Niklas Ravaja; Samuel Kaski; Giulio Jacucci (BCIforReal@IUI, 2017)

Interactive Elicitation of Knowledge on Feature Relevance Improves Predictions in Small Data Sets. - Luana Micallef; Iiris Sundin; Pekka Marttinen; Muhammad Ammad-ud-din; Tomi Peltola; Marta Soare; Giulio Jacucci; Samuel Kaski (IUI, 2017)

Convex Factorization Machine for Toxicogenomics Prediction. - Makoto Yamada; Wenzhao Lian; Amit Goyal 001; Jianhui Chen; Kishan Wimalawarne; Suleiman A. Khan; Samuel Kaski; Hiroshi Mamitsuka; Yi Chang 001 (KDD, 2017)

Differentially private Bayesian learning on distributed data. - Mikko A. Heikkilä; Eemil Lagerspetz; Samuel Kaski; Kana Shimizu; Sasu Tarkoma; Antti Honkela (NIPS, 2017)

Non-Stationary Spectral Kernels. - Sami Remes; Markus Heinonen; Samuel Kaski (NIPS, 2017)

Probabilistic Expert Knowledge Elicitation of Feature Relevances in Sparse Linear Regression. - Pedram Daee; Tomi Peltola; Marta Soare; Samuel Kaski (IAL@PKDD/ECML, 2017)

Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction. - Homayun Afrabandpey; Tomi Peltola; Samuel Kaski (UMAP, 2017)

MediSyn: uncertainty-aware visualization of multiple biomedical datasets to support drug treatment selection. - Chen He 003; Luana Micallef; ZiaurRehman Tanoli; Samuel Kaski; Tero Aittokallio; Giulio Jacucci (BMC Bioinform., 2017)

Differentially Private Bayesian Learning on Distributed Data. - Mikko A. Heikkilä; Yusuke Okimoto; Samuel Kaski; Kana Shimizu; Antti Honkela (CoRR, 2017)

Distributed Bayesian Matrix Factorization with Minimal Communication. - Xiangju Qin; Paul Blomstedt; Eemeli Leppäaho; Pekka Parviainen; Samuel Kaski (CoRR, 2017)

Improving drug sensitivity predictions in precision medicine through active expert knowledge elicitation. - Iiris Sundin; Tomi Peltola; Muntasir Mamun Majumder; Pedram Daee; Marta Soare; Homayun Afrabandpey; Caroline Heckman; Samuel Kaski; Pekka Marttinen (CoRR, 2017)

Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation. - Makoto Yamada; Song Liu 002; Samuel Kaski (CoRR, 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 structures of Bayesian networks for variable groups. - Pekka Parviainen; Samuel Kaski (Int. J. Approx. Reason., 2017)

GFA: Exploratory Analysis of Multiple Data Sources with Group Factor Analysis. - Eemeli Leppäaho; Muhammad Ammad-ud-din; Samuel Kaski (J. Mach. Learn. Res., 2017)

Multi-view kernel completion. - Sahely Bhadra; Samuel Kaski; Juho Rousu (Mach. Learn., 2017)

Knowledge elicitation via sequential probabilistic inference for high-dimensional prediction. - Pedram Daee; Tomi Peltola; Marta Soare; Samuel Kaski (Mach. Learn., 2017)

Self-Organizing Maps. - Samuel Kaski (Encyclopedia of Machine Learning and Data Mining, 2017)

Probabilistic Formulation of the Take The Best Heuristic. - Tomi Peltola; Jussi Jokinen; Samuel Kaski (CogSci, 2018)

User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction. - Pedram Daee; Tomi Peltola; Aki Vehtari; Samuel Kaski (IUI, 2018)

Variational zero-inflated Gaussian processes with sparse kernels. - Pashupati Hegde; Markus Heinonen; Samuel Kaski (UAI, 2018)

Improving genomics-based predictions for precision medicine through active elicitation of expert knowledge. - Iiris Sundin; Tomi Peltola; Luana Micallef; Homayun Afrabandpey; Marta Soare; Muntasir Mamun Majumder; Pedram Daee; Chen He 003; Baris Serim; Aki S. Havulinna; Caroline Heckman; Giulio Jacucci; et al. (Bioinform., 2018)

Modelling User's Theory of AI's Mind in Interactive Intelligent Systems. - Tomi Peltola; Mustafa Mert Çelikok; Pedram Daee; Samuel Kaski (CoRR, 2018)

Approximate Bayesian Computation via Population Monte Carlo and Classification. - Charlie Rogers-Smith; Henri Pesonen; Samuel Kaski (CoRR, 2018)

Neural Non-Stationary Spectral Kernel. - Sami Remes; Markus Heinonen; Samuel Kaski (CoRR, 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)

Inverse reinforcement learning from summary data. - Antti Kangasrääsiö; Samuel Kaski (Mach. Learn., 2018)

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

Interactive Intent Modeling for Exploratory Search. - Tuukka Ruotsalo; Jaakko Peltonen; Manuel J. A. Eugster; Dorota Glowacka; Patrik Floréen; Petri Myllymäki; Giulio Jacucci; Samuel Kaski (ACM Trans. Inf. Syst., 2018)

Deep learning with differential Gaussian process flows. - Pashupati Hegde; Markus Heinonen; Harri Lähdesmäki; Samuel Kaski (AISTATS, 2019)

Harmonizable mixture kernels with variational Fourier features. - Zheyang Shen; Markus Heinonen; Samuel Kaski (AISTATS, 2019)

Active Learning for Decision-Making from Imbalanced Observational Data. - Iiris Sundin; Peter Schulam; Eero Siivola; Aki Vehtari; Suchi Saria; Samuel Kaski (ICML, 2019)

Human-in-the-loop Active Covariance Learning for Improving Prediction in Small Data Sets. - Homayun Afrabandpey; Tomi Peltola; Samuel Kaski (IJCAI, 2019)

Scalable Bayesian Non-linear Matrix Completion. - Xiangju Qin; Paul Blomstedt; Samuel Kaski (IJCAI, 2019)

Learning Image Relations with Contrast Association Networks. - Yao Lu; Zhirong Yang; Juho Kannala; Samuel Kaski (IJCNN, 2019)

Machine Teaching of Active Sequential Learners. - Tomi Peltola; Mustafa Mert Çelikok; Pedram Daee; Samuel Kaski (NeurIPS, 2019)

Deep Convolutional Gaussian Processes. - Kenneth Blomqvist; Samuel Kaski; Markus Heinonen (ECML/PKDD (2), 2019)

Embarrassingly Parallel MCMC using Deep Invertible Transformations. - Diego Mesquita; Paul Blomstedt; Samuel Kaski (UAI, 2019)

Block HSIC Lasso: model-free biomarker detection for ultra-high dimensional data. - Héctor Climente-González; Chloé-Agathe Azencott; Samuel Kaski; Makoto Yamada (Bioinform., 2019)

Modelling G×E with historical weather information improves genomic prediction in new environments. - Jussi Gillberg; Pekka Marttinen; Hiroshi Mamitsuka; Samuel Kaski (Bioinform., 2019)

Bayesian metabolic flux analysis reveals intracellular flux couplings. - Markus Heinonen; Maria Osmala; Henrik Mannerström; Janne Wallenius; Samuel Kaski; Juho Rousu; Harri Lähdesmäki (Bioinform., 2019)

Representation transfer for differentially private drug sensitivity prediction. - Teppo Mikael Niinimäki; Mikko A. Heikkilä; Antti Honkela; Samuel Kaski (Bioinform., 2019)

Parameter Inference for Computational Cognitive Models with Approximate Bayesian Computation. - Antti Kangasrääsiö; Jussi P. P. Jokinen; Antti Oulasvirta; Andrew Howes 001; Samuel Kaski (Cogn. Sci., 2019)

Recovering Pairwise Interactions Using Neural Networks. - Tianyu Cui; Pekka Marttinen; Samuel Kaski (CoRR, 2019)

Making Bayesian Predictive Models Interpretable: A Decision Theoretic Approach. - Homayun Afrabandpey; Tomi Peltola; Juho Piironen; Aki Vehtari; Samuel Kaski (CoRR, 2019)

Privacy-preserving data sharing via probabilistic modelling. - Joonas Jälkö; Eemil Lagerspetz; Jari Haukka; Sasu Tarkoma; Samuel Kaski; Antti Honkela (CoRR, 2019)

Interactive AI with a Theory of Mind. - Mustafa Mert Çelikok; Tomi Peltola; Pedram Daee; Samuel Kaski (CoRR, 2019)

Integrating neurophysiologic relevance feedback in intent modeling for information retrieval. - Giulio Jacucci; Oswald Barral; Pedram Daee; Markus Wenzel 002; Baris Serim; Tuukka Ruotsalo; Patrik Pluchino; Jonathan Freeman; Luciano Gamberini; Samuel Kaski; Benjamin Blankertz (J. Assoc. Inf. Sci. Technol., 2019)

Distributed Bayesian matrix factorization with limited communication. - Xiangju Qin; Paul Blomstedt; Eemeli Leppäaho; Pekka Parviainen; Samuel Kaski (Mach. Learn., 2019)

Scalable Probabilistic Matrix Factorization with Graph-Based Priors. - Jonathan Strahl; Jaakko Peltonen; Hiroshi Mamitsuka; Samuel Kaski (AAAI, 2020)

Learning spectrograms with convolutional spectral kernels. - Zheyang Shen; Markus Heinonen; Samuel Kaski (AISTATS, 2020)

Learning Global Pairwise Interactions with Bayesian Neural Networks. - Tianyu Cui; Pekka Marttinen; Samuel Kaski (ECAI, 2020)

A High-Performance Implementation of Bayesian Matrix Factorization with Limited Communication. - Tom Vander Aa; Xiangju Qin; Paul Blomstedt; Roel Wuyts; Wilfried Verachtert; Samuel Kaski (ICCS (6), 2020)

Projective Preferential Bayesian Optimization. - Petrus Mikkola; Milica Todorovic; Jari Järvi; Patrick Rinke; Samuel Kaski (ICML, 2020)

Rethinking pooling in graph neural networks. - Diego Mesquita; Amauri H. Souza Jr.; Samuel Kaski (NeurIPS, 2020)

Human Strategic Steering Improves Performance of Interactive Optimization. - Fabio Colella; Pedram Daee; Jussi Jokinen; Antti Oulasvirta; Samuel Kaski (UMAP, 2020)

Informative Gaussian Scale Mixture Priors for Bayesian Neural Networks. - Tianyu Cui; Aki S. Havulinna; Pekka Marttinen; Samuel Kaski (CoRR, 2020)

Correlated Feature Selection with Extended Exclusive Group Lasso. - Yuxin Sun; Benny Chain; Samuel Kaski; John Shawe-Taylor (CoRR, 2020)

Variance reduction for distributed stochastic gradient MCMC. - Khaoula el Mekkaoui; Diego Mesquita; Paul Blomstedt; Samuel Kaski (CoRR, 2020)

Differentially private cross-silo federated learning. - Mikko A. Heikkilä; Antti Koskela; Kana Shimizu; Samuel Kaski; Antti Honkela (CoRR, 2020)

Teaching to Learn: Sequential Teaching of Agents with Inner States. - Mustafa Mert Çelikok; Pierre-Alexandre Murena; Samuel Kaski (CoRR, 2020)

Privacy-preserving Data Sharing on Vertically Partitioned Data. - Razane Tajeddine; Joonas Jälkö; Samuel Kaski; Antti Honkela (CoRR, 2020)

Scalable Bayesian neural networks by layer-wise input augmentation. - Trung Q. Trinh; Samuel Kaski; Markus Heinonen (CoRR, 2020)

Sample-efficient reinforcement learning using deep Gaussian processes. - Charles W. L. Gadd; Markus Heinonen; Harri Lähdesmäki; Samuel Kaski (CoRR, 2020)

Interactive faceted query suggestion for exploratory search: Whole-session effectiveness and interaction engagement. - Tuukka Ruotsalo; Giulio Jacucci; Samuel Kaski (J. Assoc. Inf. Sci. Technol., 2020)

A decision-theoretic approach for model interpretability in Bayesian framework. - Homayun Afrabandpey; Tomi Peltola; Juho Piironen; Aki Vehtari; Samuel Kaski (Mach. Learn., 2020)

Local dimension reduction of summary statistics for likelihood-free inference. - Jukka Sirén; Samuel Kaski (Stat. Comput., 2020)

Bayesian Inference for Optimal Transport with Stochastic Cost. - Anton Mallasto; Markus Heinonen; Samuel Kaski (ACML, 2021)

Learning to Assist Agents by Observing Them. - Antti Keurulainen; Isak Westerlund; Samuel Kaski; Alexander Ilin (ICANN (4), 2021)

Behaviour-Conditioned Policies for Cooperative Reinforcement Learning Tasks. - Antti Keurulainen; Isak Westerlund; Ariel Kwiatkowski; Samuel Kaski; Alexander Ilin (ICANN (4), 2021)

Differentially Private Bayesian Inference for Generalized Linear Models. - Tejas Kulkarni; Joonas Jälkö; Antti Koskela; Samuel Kaski; Antti Honkela (ICML, 2021)

Decision Rule Elicitation for Domain Adaptation. - Alexander V. Nikitin; Samuel Kaski (IUI, 2021)

De-randomizing MCMC dynamics with the diffusion Stein operator. - Zheyang Shen; Markus Heinonen; Samuel Kaski (NeurIPS, 2021)

EntityBot: Supporting Everyday Digital Tasks with Entity Recommendations. - Vuong Thanh Tung; Salvatore Andolina; Giulio Jacucci; Pedram Daee; Khalil Klouche; Mats Sjöberg; Tuukka Ruotsalo; Samuel Kaski (RecSys, 2021)

Federated stochastic gradient Langevin dynamics. - Khaoula el Mekkaoui; Diego Mesquita; Paul Blomstedt; Samuel Kaski (UAI, 2021)

Machine learning approaches for drug combination therapies. - Betül Güvenç Paltun; Samuel Kaski; Hiroshi Mamitsuka (Briefings Bioinform., 2021)

Improving drug response prediction by integrating multiple data sources: matrix factorization, kernel and network-based approaches. - Betül Güvenç Paltun; Hiroshi Mamitsuka; Samuel Kaski (Briefings Bioinform., 2021)

Affine Transport for Sim-to-Real Domain Adaptation. - Anton Mallasto; Karol Arndt; Markus Heinonen; Samuel Kaski; Ville Kyrki (CoRR, 2021)

Bayesian inference of ODEs with Gaussian processes. - Pashupati Hegde; Çagatay Yildiz; Harri Lähdesmäki; Samuel Kaski; Markus Heinonen (CoRR, 2021)

Locally Differentially Private Bayesian Inference. - Tejas Kulkarni; Joonas Jälkö; Samuel Kaski; Antti Honkela (CoRR, 2021)

Privacy-preserving data sharing via probabilistic modeling. - Joonas Jälkö; Eemil Lagerspetz; Jari Haukka; Sasu Tarkoma; Antti Honkela; Samuel Kaski (Patterns, 2021)

Entity Recommendation for Everyday Digital Tasks. - Giulio Jacucci; Pedram Daee; Tung Thanh Vuong; Salvatore Andolina; Khalil Klouche; Mats Sjöberg; Tuukka Ruotsalo; Samuel Kaski (ACM Trans. Comput. Hum. Interact., 2021)

Non-separable Spatio-temporal Graph Kernels via SPDEs. - Alexander V. Nikitin; S. T. John; Arno Solin; Samuel Kaski (AISTATS, 2022)

Parallel MCMC Without Embarrassing Failures. - Daniel Augusto de Souza; Diego Mesquita; Samuel Kaski; Luigi Acerbi (AISTATS, 2022)

Best-Response Bayesian Reinforcement Learning with Bayes-adaptive POMDPs for Centaurs. - Mustafa Mert Çelikok; Frans A. Oliehoek; Samuel Kaski (AAMAS, 2022)

EntityBot: Actionable Entity Recommendations for Everyday Digital Task. - Tung Thanh Vuong; Salvatore Andolina; Giulio Jacucci; Pedram Daee; Khalil Klouche; Mats Sjöberg; Tuukka Ruotsalo; Samuel Kaski (CHI Extended Abstracts, 2022)

Approximate Bayesian Computation with Domain Expert in the Loop. - Ayush Bharti; Louis Filstroff; Samuel Kaski (ICML, 2022)

Tackling covariate shift with node-based Bayesian neural networks. - Trung Q. Trinh; Markus Heinonen; Luigi Acerbi; Samuel Kaski (ICML, 2022)

Human-in-the-Loop Large-Scale Predictive Maintenance of Workstations. - Alexander V. Nikitin; Samuel Kaski (KDD, 2022)

Deconfounded Representation Similarity for Comparison of Neural Networks. - Tianyu Cui; Yogesh Kumar; Pekka Marttinen; Samuel Kaski (NeurIPS, 2022)

Provably expressive temporal graph networks. - Amauri H. Souza; Diego Mesquita; Samuel Kaski; Vikas Garg 001 (NeurIPS, 2022)

Modular Flows: Differential Molecular Generation. - Yogesh Verma; Samuel Kaski; Markus Heinonen; Vikas Garg 001 (NeurIPS, 2022)

Variational multiple shooting for Bayesian ODEs with Gaussian processes. - Pashupati Hegde; Çagatay Yildiz; Harri Lähdesmäki; Samuel Kaski; Markus Heinonen (UAI, 2022)

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)

Zero-Shot Assistance in Novel Decision Problems. - Sebastiaan De Peuter; Samuel Kaski (CoRR, 2022)

Bayesian Optimization Augmented with Actively Elicited Expert Knowledge. - Daolang Huang; Louis Filstroff; Petrus Mikkola; Runkai Zheng; Samuel Kaski (CoRR, 2022)

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

Human-in-the-loop assisted de novo molecular design. - Iiris Sundin; Alexey Voronov; Haoping Xiao; Kostas Papadopoulos; Esben Jannik Bjerrum; Markus Heinonen; Atanas Patronov; Samuel Kaski; Ola Engkvist (J. Cheminformatics, 2022)

d3p - A Python Package for Differentially-Private Probabilistic Programming. - Lukas Prediger; Niki Andreas Lopi; Samuel Kaski; Antti Honkela (Proc. Priv. Enhancing Technol., 2022)

DIVERSE: Bayesian Data IntegratiVE Learning for Precise Drug ResponSE Prediction. - Betül Güvenç Paltun; Samuel Kaski; Hiroshi Mamitsuka (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

Teaching to Learn: Sequential Teaching of Learners with Internal States. - Mustafa Mert Çelikok; Pierre-Alexandre Murena; Samuel Kaski (AAAI, 2023)

Zero-Shot Assistance in Sequential Decision Problems. - Sebastiaan De Peuter; Samuel Kaski (AAAI, 2023)

Multi-Fidelity Bayesian Optimization with Unreliable Information Sources. - Petrus Mikkola; Julien Martinelli; Louis Filstroff; Samuel Kaski (AISTATS, 2023)

Noise-Aware Statistical Inference with Differentially Private Synthetic Data. - Ossi Räisä; Joonas Jälkö; Samuel Kaski; Antti Honkela (AISTATS, 2023)

Optimally-weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference. - Ayush Bharti; Masha Naslidnyk; Oscar Key; Samuel Kaski; François-Xavier Briol (ICML, 2023)

Imitation-Guided Multimodal Policy Generation from Behaviourally Diverse Demonstrations. - Shibei Zhu; Rituraj Kaushik; Samuel Kaski; Ville Kyrki (IROS, 2023)

Characterizing personalized effects of family information on disease risk using graph representation learning. - Sophie Wharrie; Zhiyu Yang; Andrea Ganna; Samuel Kaski (MLHC, 2023)

Compositional Sculpting of Iterative Generative Processes. - Timur Garipov; Sebastiaan De Peuter; Ge Yang 003; Vikas Garg 001; Samuel Kaski; Tommi S. Jaakkola (NeurIPS, 2023)

Learning Robust Statistics for Simulation-based Inference under Model Misspecification. - Daolang Huang; Ayush Bharti; Amauri H. Souza; Luigi Acerbi; Samuel Kaski (NeurIPS, 2023)

Practical Equivariances via Relational Conditional Neural Processes. - Daolang Huang; Manuel Haussmann; Ulpu Remes; St John; Grégoire Clarté; Kevin Sebastian Luck; Samuel Kaski; Luigi Acerbi (NeurIPS, 2023)

Cooperative Bayesian Optimization for Imperfect Agents. - Ali Khoshvishkaie; Petrus Mikkola; Pierre-Alexandre Murena; Samuel Kaski (ECML/PKDD (1), 2023)

Differentiable user models. - Alex Hämäläinen; Mustafa Mert Çelikok; Samuel Kaski (UAI, 2023)

Online simulator-based experimental design for cognitive model selection. - Alexander Aushev; Aini Putkonen; Gregoire Clarte; Suyog Chandramouli; Luigi Acerbi; Samuel Kaski; Andrew Howes 001 (CoRR, 2023)

Cost-aware learning of relevant contextual variables within Bayesian optimization. - Julien Martinelli; Ayush Bharti; S. T. John; Armi Tiihonen; Sabina Sloman; Louis Filstroff; Samuel Kaski (CoRR, 2023)

Input gradient diversity for neural network ensembles. - Trung Q. Trinh; Markus Heinonen; Luigi Acerbi; Samuel Kaski (CoRR, 2023)

Practical Equivariances via Relational Conditional Neural Processes. - Daolang Huang; Manuel Haussmann; Ulpu Remes; S. T. John; Grégoire Clarté; Kevin Sebastian Luck; Samuel Kaski; Luigi Acerbi (CoRR, 2023)

Collaborative Learning From Distributed Data With Differentially Private Synthetic Twin Data. - Lukas Prediger; Joonas Jälkö; Antti Honkela; Samuel Kaski (CoRR, 2023)

Human-in-the-Loop Causal Discovery under Latent Confounding using Ancestral GFlowNets. - Tiago da Silva; Eliezer S. Silva; Adèle H. Ribeiro; António Góis; Dominik Heider; Samuel Kaski; Diego Mesquita (CoRR, 2023)

Understanding deep neural networks through the lens of their non-linearity. - Quentin Bouniot; Ievgen Redko; Anton Mallasto; Charlotte Laclau; Karol Arndt; Oliver Struckmeier; Markus Heinonen; Ville Kyrki; Samuel Kaski (CoRR, 2023)

Causal Similarity-Based Hierarchical Bayesian Models. - Sophie Wharrie; Samuel Kaski (CoRR, 2023)

The Fundamental Dilemma of Bayesian Active Meta-learning. - Sabina J. Sloman; Ayush Bharti; Samuel Kaski (CoRR, 2023)

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

DPVIm: Differentially Private Variational Inference Improved. - Joonas Jälkö; Lukas Prediger; Antti Honkela; Samuel Kaski (Trans. Mach. Learn. Res., 2023)

Modeling needs user modeling. - Mustafa Mert Çelikok; Pierre-Alexandre Murena; Samuel Kaski (Frontiers Artif. Intell., 2023)

Toward AI assistants that let designers design. - Sebastiaan De Peuter; Antti Oulasvirta; Samuel Kaski (AI Mag., 2023)

Intelligent digital tools for screening of brain connectivity and dementia risk estimation in people affected by mild cognitive impairment: the AI-Mind clinical study protocol. - Ira R. J. Hebold Haraldsen; Christoffer Hatlestad-Hall; Camillo Marra; Hanna Renvall; Fernando Maestú; Jorge Acosta-Hernández; Soraya Alfonsin; Vebjørn Andersson; Abhilash Anand; Victor Ayllón; Aleksandar Babic; Asma Belhadi; et al. (Frontiers Neurorobotics, 2023)

HAPNEST: efficient, large-scale generation and evaluation of synthetic datasets for genotypes and phenotypes. - Sophie Wharrie; Zhiyu Yang; Vishnu Raj; Remo Monti; Rahul Gupta; Ying Wang 074; Alicia Martin; Luke J. O'Connor; Samuel Kaski; Pekka Marttinen; Pier Francesco Palamara; Christoph Lippert; et al. (Bioinform., 2023)

The influence of inter-regional delays in generating large-scale brain networks of phase synchronization. - Nitin Williams; A. Ojanperä; Felix Siebenhühner; Benedetta Toselli; Satu Palva; Gabriele Arnulfo; Samuel Kaski; J. Matias Palva (NeuroImage, 2023)

Estimating treatment effects from single-arm trials via latent-variable modeling. - Manuel Haussmann; Tran Minh Son Le; Viivi Halla-aho; Samu Kurki; Jussi Leinonen; Miika Koskinen; Samuel Kaski; Harri Lähdesmäki (AISTATS, 2024)

Uncoupled Learning of Differential Stackelberg Equilibria with Commitments. - Robert T. Loftin; Mustafa Mert Çelikok; Herke van Hoof; Samuel Kaski; Frans A. Oliehoek (AAMAS, 2024)

Deep Bayesian Experimental Design for Drug Discovery. - Muhammad Arslan Masood; Tianyu Cui; Samuel Kaski (AIDD@ICANN, 2024)

Balancing Imbalanced Toxicity Models: Using MolBERT with Focal Loss. - Muhammad Arslan Masood; Samuel Kaski; Hugo Ceulemans; Dorota Herman; Markus Heinonen (AIDD@ICANN, 2024)

Towards Interpretable Models of Chemist Preferences for Human-in-the-Loop Assisted Drug Discovery. - Yasmine Nahal; Markus Heinonen; Mikhail Kabeshov; Jon Paul Janet; Eva Nittinger; Ola Engkvist; Samuel Kaski (AIDD@ICANN, 2024)

Input-gradient space particle inference for neural network ensembles. - Trung Q. Trinh; Markus Heinonen; Luigi Acerbi; Samuel Kaski (ICLR, 2024)

Embarrassingly Parallel GFlowNets. - Tiago da Silva; Luiz Max Carvalho; Amauri H. Souza; Samuel Kaski; Diego Mesquita (ICML, 2024)

Open Ad Hoc Teamwork with Cooperative Game Theory. - Jianhong Wang; Yang Li 116; Yuan Zhang 027; Wei Pan 004; Samuel Kaski (ICML, 2024)

Amortized Bayesian Experimental Design for Decision-Making. - Daolang Huang; Yujia Guo; Luigi Acerbi; Samuel Kaski (NeurIPS, 2024)

TSGM: A Flexible Framework for Generative Modeling of Synthetic Time Series. - Alexander V. Nikitin; Letizia Iannucci; Samuel Kaski (NeurIPS, 2024)

Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice. - Sebastiaan De Peuter; Shibei Zhu; Yujia Guo; Andrew Howes 001; Samuel Kaski (NeurIPS, 2024)

Improving robustness to corruptions with multiplicative weight perturbations. - Trung Q. Trinh; Markus Heinonen; Luigi Acerbi; Samuel Kaski (NeurIPS, 2024)

Learning relevant contextual variables within Bayesian optimization. - Julien Martinelli; Ayush Bharti; Armi Tiihonen; S. T. John; Louis Filstroff; Sabina J. Sloman; Patrick Rinke; Samuel Kaski (UAI, 2024)

Bayesian Active Learning in the Presence of Nuisance Parameters. - Sabina J. Sloman; Ayush Bharti; Julien Martinelli; Samuel Kaski (UAI, 2024)

Online Learning of Human Constraints from Feedback in Shared Autonomy. - Shibei Zhu; Tran Nguyen Le; Samuel Kaski; Ville Kyrki (CoRR, 2024)

In-n-Out: Calibrating Graph Neural Networks for Link Prediction. - Erik Nascimento; Diego Mesquita; Samuel Kaski; Amauri H. Souza (CoRR, 2024)

Heteroscedastic Preferential Bayesian Optimization with Informative Noise Distributions. - Marshal Arijona Sinaga; Julien Martinelli; Vikas Garg 001; Samuel Kaski (CoRR, 2024)

Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games. - Anjie Liu; Jianhong Wang; Haoxuan Li 001; Xu Chen 017; Jun Wang 012; Samuel Kaski; Mengyue Yang (CoRR, 2024)

Improving robustness to corruptions with multiplicative weight perturbations. - Trung Trinh; Markus Heinonen; Luigi Acerbi; Samuel Kaski (CoRR, 2024)

Transformer Normalisation Layers and the Independence of Semantic Subspaces. - Stephen Menary; Samuel Kaski; Andre Freitas (CoRR, 2024)

What Ails Generative Structure-based Drug Design: Too Little or Too Much Expressivity? - Rafal Karczewski; Samuel Kaski; Markus Heinonen; Vikas Garg 001 (CoRR, 2024)

DroneDiffusion: Robust Quadrotor Dynamics Learning with Diffusion Models. - Avirup Das; Rishabh Dev Yadav; Sihao Sun; Mingfei Sun 001; Samuel Kaski; Wei Pan 004 (CoRR, 2024)

Identifying latent disease factors differently expressed in patient subgroups using group factor analysis. - Fabio S. Ferreira; John Ashburner; Arabella Bouzigues; Chatrin Suksasilp; Lucy L. Russell; Phoebe H. Foster; Eve Ferry-Bolder; John C. van Swieten; Lize C. Jiskoot; Harro Seelaar; Raquel Sánchez-Valle; Robert Laforce; et al. (CoRR, 2024)

LoKO: Low-Rank Kalman Optimizer for Online Fine-Tuning of Large Models. - Hossein Abdi; Mingfei Sun 001; Andi Zhang 001; Samuel Kaski; Wei Pan 004 (CoRR, 2024)

Amortized Probabilistic Conditioning for Optimization, Simulation and Inference. - Paul E. Chang; Nasrulloh Loka; Daolang Huang; Ulpu Remes; Samuel Kaski; Luigi Acerbi (CoRR, 2024)

Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model. - Hans Moen; Vishnu Raj; Andrius Vabalas; Markus Perola; Samuel Kaski; Andrea Ganna; Pekka Marttinen (CoRR, 2024)

Targeted Active Learning for Bayesian Decision-Making. - Louis Filstroff; Iiris Sundin; Petrus Mikkola; Aleksei Tiulpin; Juuso Kylmäoja; Samuel Kaski (Trans. Mach. Learn. Res., 2024)

Likelihood-free inference in state-space models with unknown dynamics. - Alexander Aushev; Thong Tran; Henri Pesonen; Andrew Howes 001; Samuel Kaski (Stat. Comput., 2024)

Entity Footprinting: Modeling Contextual User States via Digital Activity Monitoring. - Zeinab R. Yousefi; Vuong Thanh Tung; Marie Al-Ghossein; Tuukka Ruotsalo; Giulio Jacucci; Samuel Kaski (ACM Trans. Interact. Intell. Syst., 2024)

Metis: a python-based user interface to collect expert feedback for generative chemistry models. - Janosch Menke; Yasmine Nahal; Esben Jannik Bjerrum; Mikhail Kabeshov; Samuel Kaski; Ola Engkvist (J. Cheminformatics, 2024)

Human-in-the-loop active learning for goal-oriented molecule generation. - Yasmine Nahal; Janosch Menke; Julien Martinelli; Markus Heinonen; Mikhail Kabeshov; Jon Paul Janet; Eva Nittinger; Ola Engkvist; Samuel Kaski (J. Cheminformatics, 2024)

Collaborative learning from distributed data with differentially private synthetic data. - Lukas Prediger; Joonas Jälkö; Antti Honkela; Samuel Kaski (BMC Medical Informatics Decis. Mak., 2024)

Cost-aware simulation-based inference. - Ayush Bharti; Daolang Huang; Samuel Kaski; François-Xavier Briol (AISTATS, 2025)

Amortized Probabilistic Conditioning for Optimization, Simulation and Inference. - Paul Edmund Chang; Nasrulloh Ratu Bagus Satrio Loka; Daolang Huang; Ulpu Remes; Samuel Kaski; Luigi Acerbi (AISTATS, 2025)

What Ails Generative Structure-based Drug Design: Expressivity is Too Little or Too Much? - Rafal Karczewski; Samuel Kaski; Markus Heinonen; Vikas K. Garg 001 (AISTATS, 2025)

From Alexnet to Transformers: Measuring the Non-linearity of Deep Neural Networks with Affine Optimal Transport. - Quentin Bouniot; Ievgen Redko; Anton Mallasto; Charlotte Laclau; Oliver Struckmeier; Karol Arndt; Markus Heinonen; Ville Kyrki; Samuel Kaski (CVPR, 2025)

When do GFlowNets learn the right distribution? - Tiago da Silva; Rodrigo Barreto Alves; Eliezer de Souza da Silva; Amauri H. Souza; Vikas Garg 001; Samuel Kaski; Diego Mesquita (ICLR, 2025)

Generalization and Distributed Learning of GFlowNets. - Tiago Silva; Amauri H. Souza; Omar Rivasplata; Vikas Garg 001; Samuel Kaski; Diego Mesquita (ICLR, 2025)

PABBO: Preferential Amortized Black-Box Optimization. - Xinyu Zhang; Daolang Huang; Samuel Kaski; Julien Martinelli (ICLR, 2025)

Proxy-informed Bayesian transfer learning with unknown sources. - Sabina J. Sloman; Julien Martinelli; Samuel Kaski (UAI, 2025)

Privacy-Preserving Neural Processes for Probabilistic User Modeling. - Amir Sonee; Haripriya Harikumar; Alex Hämäläinen; Lukas Prediger; Samuel Kaski (UAI, 2025)

Video-Language Critic: Transferable Reward Functions for Language-Conditioned Robotics. - Minttu Alakuijala; Reginald McLean; Isaac Woungang; Nariman Farsad; Samuel Kaski; Pekka Marttinen; Kai Yuan (Trans. Mach. Learn. Res., 2025)

Memento No More: Coaching AI Agents to Master Multiple Tasks via Hints Internalization. - Minttu Alakuijala; Ya Gao 005; Georgy Ananov; Samuel Kaski; Pekka Marttinen; Alexander Ilin; Harri Valpola (CoRR, 2025)

Robust and Computation-Aware Gaussian Processes. - Marshal Arijona Sinaga; Julien Martinelli; Samuel Kaski (CoRR, 2025)

Epistemic Errors of Imperfect Multitask Learners When Distributions Shift. - Sabina J. Sloman; Michele Caprio; Samuel Kaski (CoRR, 2025)

ALINE: Joint Amortization for Bayesian Inference and Active Data Acquisition. - Daolang Huang; Xinyi Wen; Ayush Bharti; Samuel Kaski; Luigi Acerbi (CoRR, 2025)

Generalization Analysis for Bayesian Optimal Experiment Design under Model Misspecification. - Roubing Tang; Sabina J. Sloman; Samuel Kaski (CoRR, 2025)

Shapley Machine: A Game-Theoretic Framework for N-Agent Ad Hoc Teamwork. - Jianhong Wang; Yang Li 116; Samuel Kaski; Jonathan Lawry (CoRR, 2025)

Concept-based Adversarial Attack: a Probabilistic Perspective. - Andi Zhang 001; Xuan Ding; Steven McDonagh; Samuel Kaski (CoRR, 2025)

Virtual Laboratories: Domain-agnostic workflows for research. - Carlos Sevilla-Salcedo; Armi Tiihonen; Mahsa Asadi; Kevin Sebastian Luck; Aras Umut Erarslan; Arto Klami; Samuel Kaski (CoRR, 2025)

Molecular property prediction using pretrained-BERT and Bayesian active learning: a data-efficient approach to drug design. - Muhammad Arslan Masood; Samuel Kaski; Tianyu Cui (J. Cheminformatics, 2025)

VitroBert: modeling DILI by pretraining BERT on in vitro data. - Muhammad Arslan Masood; Anamya Ajjolli Nagaraja; Katia Belaid; Natalie Mesens; Hugo Ceulemans; Samuel Kaski; Dorota Herman; Markus Heinonen (J. Cheminformatics, 2025)

E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays. - Vincenzo Palmacci; Yasmine Nahal; Matthias Welsch; Ola Engkvist; Samuel Kaski; Johannes Kirchmair (J. Cheminformatics, 2025)