Regression with n$\to$1 by Expert Knowledge Elicitation

Marta Soare, Muhammad Ammad-ud-din, Samuel Kaski

Interactive Modeling of Concept Drift and Errors in Relevance Feedback

Antti Kangasrääsiö, Yi Chen, Dorota Głowacka +1

Inverse Reinforcement Learning from Summary Data

Antti Kangasrääsiö, Samuel Kaski

Retrieval of Experiments by Efficient Estimation of Marginal Likelihood

Sohan Seth, John Shawe-Taylor, Samuel Kaski

PinView: Implicit Feedback in Content-Based Image Retrieval

Zakria Hussain, Arto Klami, Jussi Kujala +6

Deep convolutional Gaussian processes

Kenneth Blomqvist, Samuel Kaski, Markus Heinonen

Learning Structures of Bayesian Networks for Variable Groups

Pekka Parviainen, Samuel Kaski

Drug response prediction by inferring pathway-response associations with Kernelized Bayesian Matrix Factorization

Muhammad Ammad-ud-din, Suleiman A. Khan, Disha Malani +4

ELFI: Engine for Likelihood-Free Inference

Jarno Lintusaari, Henri Vuollekoski, Antti Kangasrääsiö +7

Bayesian Group Factor Analysis

Seppo Virtanen, Arto Klami, Suleiman A. Khan +1

RPA: Probabilistic analysis of probe performance and robust summarization

Leo Lahti, Laura L. Elo, Tero Aittokallio +1

Active Learning for Decision-Making from Imbalanced Observational Data

Iiris Sundin, Peter Schulam, Eero Siivola +3

Retrieval of Experiments with Sequential Dirichlet Process Mixtures in Model Space

Ritabrata Dutta, Sohan Seth, Samuel Kaski

Bayesian exponential family projections for coupled data sources

Arto Klami, Seppo Virtanen, Samuel Kaski

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

Homayun Afrabandpey, Tomi Peltola, Samuel Kaski

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

Luana Micallef, Iiris Sundin, Pekka Marttinen +5

Likelihood-free inference via classification

Michael U. Gutmann, Ritabrata Dutta, Samuel Kaski +1

Convex Factorization Machine for Regression

Makoto Yamada, Wenzhao Lian, Amit Goyal +6

Deep learning with differential Gaussian process flows

Pashupati Hegde, Markus Heinonen, Harri Lähdesmäki +1

Genome-wide association studies with high-dimensional phenotypes

Pekka Marttinen, Jussi Gillberg, Aki Havulinna +2

Inferring Cognitive Models from Data using Approximate Bayesian Computation

Antti Kangasrääsiö, Kumaripaba Athukorala, Andrew Howes +3

Stronger findings from mass spectral data through multi-peak modeling

Tommi Suvitaival, Simon Rogers, Samuel Kaski

Sparse group factor analysis for biclustering of multiple data sources

Kerstin Bunte, Eemeli Leppäaho, Inka Saarinen +1

Differentially Private Bayesian Learning on Distributed Data

Mikko Heikkilä, Eemil Lagerspetz, Samuel Kaski +3

Dependency detection with similarity constraints

Leo Lahti, Samuel Myllykangas, Sakari Knuutila +1

Global modeling of transcriptional responses in interaction networks

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

Variational zero-inflated Gaussian processes with sparse kernels

Pashupati Hegde, Markus Heinonen, Samuel Kaski

Localized Lasso for High-Dimensional Regression

Makoto Yamada, Koh Takeuchi, Tomoharu Iwata +2

Classification and Bayesian Optimization for Likelihood-Free Inference

Michael U. Gutmann, Jukka Corander, Ritabrata Dutta +1

Kernelized Bayesian Matrix Factorization

Mehmet Gönen, Suleiman A. Khan, Samuel Kaski

Translating biomarkers between multi-way time-series experiments

Ilkka Huopaniemi, Tommi Suvitaival, Matej Orešič +1

Scalable Bayesian Non-linear Matrix Completion

Xiangju Qin, Paul Blomstedt, Samuel Kaski

The paper proposes a scalable Bayesian algorithm for non‑linear matrix completion using Gaussian process latent variable models and a data‑parallel distributed implementation.

Neural Non-Stationary Spectral Kernel

Sami Remes, Markus Heinonen, Samuel Kaski

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

Eemeli Leppäaho, Muhammad Ammad-ud-din, Samuel Kaski

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

Jussi Gillberg, Pekka Marttinen, Matti Pirinen +5

Efficient differentially private learning improves drug sensitivity prediction

Antti Honkela, Mrinal Das, Arttu Nieminen +2

Bayesian multi-tensor factorization

Suleiman A. Khan, Eemeli Leppäaho, Samuel Kaski

Bayesian inference in hierarchical models by combining independent posteriors

Ritabrata Dutta, Paul Blomstedt, Samuel Kaski

Inference with Discriminative Posterior

Jarkko Salojärvi, Kai Puolamäki, Eerika Savia +1

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

Paul Blomstedt, Ritabrata Dutta, Sohan Seth +2

Knowledge Elicitation via Sequential Probabilistic Inference for High-Dimensional Prediction

Pedram Daee, Tomi Peltola, Marta Soare +1

Component models for large networks

Janne Sinkkonen, Janne Aukia, Samuel Kaski

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

Sami Remes, Tommi Mononen, Samuel Kaski

Toward computational cumulative biology by combining models of biological datasets

Ali Faisal, Jaakko Peltonen, Elisabeth Georgii +2

Non-Stationary Gaussian Process Regression with Hamiltonian Monte Carlo

Markus Heinonen, Henrik Mannerström, Juho Rousu +2

Two-Way Latent Grouping Model for User Preference Prediction

Eerika Savia, Kai Puolamaki, Janne Sinkkonen +1

Bayesian Metabolic Flux Analysis reveals intracellular flux couplings

Markus Heinonen, Maria Osmala, Henrik Mannerström +4

Interpreting Outliers: Localized Logistic Regression for Density Ratio Estimation

Makoto Yamada, Song Liu, Samuel Kaski

Natural brain-information interfaces: Recommending information by relevance inferred from human brain signals

Manuel J. A. Eugster, Tuukka Ruotsalo, Michiel M. Spapé +4

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

Iiris Sundin, Tomi Peltola, Muntasir Mamun Majumder +6

Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction

Homayun Afrabandpey, Tomi Peltola, Samuel Kaski

Multiple Output Regression with Latent Noise

Jussi Gillberg, Pekka Marttinen, Matti Pirinen +7

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 Patric Mpindi +6

Multi-view Kernel Completion

Sahely Bhadra, Samuel Kaski, Juho Rousu

Visualizations Relevant to The User By Multi-View Latent Variable Factorization

Seppo Virtanen, Homayun Afrabandpey, Samuel Kaski

Exploration and retrieval of whole-metagenome sequencing samples

Sohan Seth, Niko Välimäki, Samuel Kaski +1

Multi-Way, Multi-View Learning

Ilkka Huopaniemi, Tommi Suvitaival, Janne Nikkilä +2

Learning Image Relations with Contrast Association Networks

Yao Lu, Zhirong Yang, Juho Kannala +1

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

Suleiman A Khan, Seppo Virtanen, Olli P Kallioniemi +3

Group Factor Analysis

Arto Klami, Seppo Virtanen, Eemeli Leppäaho +1

Local dimension reduction of summary statistics for likelihood-free inference

Jukka Sirén, Samuel Kaski

User Modelling for Avoiding Overfitting in Interactive Knowledge Elicitation for Prediction

Pedram Daee, Tomi Peltola, Aki Vehtari +1

A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings

Sami Remes, Markus Heinonen, Samuel Kaski