P. Blomstedt

发表

Expectation Propagation as a Way of Life

J. Cunningham, C. Robert, A. Gelman, 2020 .

Bayesian inference in hierarchical models by combining independent posteriors

Ritabrata Dutta, Samuel Kaski, P. Blomstedt, 2016, 1603.09272.

Meta-analysis of Bayesian analyses.

Jarno Lintusaari, Samuel Kaski, J. Corander, 2019, 1904.04484.

Supplement: Meta-analysis of Bayesian analyses

P. Blomstedt, Diego Mesquita, 2019 .

Resolving outbreak dynamics using approximate Bayesian computation for stochastic birth–death models

M. Gutmann, Jarno Lintusaari, Samuel Kaski, 2019, Wellcome Open Research.

A Bayesian length-based population dynamics model for northern shrimp (Pandalus Borealis)

J. Vanhatalo, P. Blomstedt, S. Mantyniemi, 2015, 1509.08774.

Early growth and non-alcoholic fatty liver disease in adulthood—the NAFLD liver fat score and equation applied on the Helsinki Birth Cohort Study

P. Blomstedt, J. Eriksson, C. Osmond, 2013, Annals of medicine.

General state-space population dynamics model for Bayesian stock assessment

Jarno Vanhatalo, Henni Pulkkinen, Samu Mäntyniemi, 2015 .

Federated stochastic gradient Langevin dynamics

Samuel Kaski, Diego Mesquita, Paul Blomstedt, 2020, Conference on Uncertainty in Artificial Intelligence.

Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data

Aki Vehtari, Andrew Gelman, John P. Cunningham, 2014, J. Mach. Learn. Res..

Bayesian predictive modeling and comparison of oil samples

Jukka Corander, Paul Blomstedt, Romain Gauriot, 2014 .

A Central Role for GRB10 in Regulation of Islet Function in Man

Mark I. McCarthy, Philippe Froguel, Jeffrey R. O'Connell, 2014, PLoS genetics.

Leukocyte telomere length and its relation to food and nutrient intake in an elderly population

P. Blomstedt, E. Moltchanova, S. Männistö, 2012, European Journal of Clinical Nutrition.

Federated stochastic gradient Langevin dynamics

Khaoula El Mekkaoui, Khaoula El Mekkaoui, Diego Mesquita, 2020, UAI.

Embarrassingly Parallel MCMC using Deep Invertible Transformations

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

A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type

Jukka Corander, Jing Tang, Jie Xiong, 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

Childhood BMI trajectories and the risk of developing young adult-onset diabetes

P. Blomstedt, J. Tuomilehto, J. Eriksson, 2009, Diabetologia.

Prenatal exposure to wartime stress – long-term effect on coronary heart disease in later life

P. Blomstedt, J. Eriksson, E. Moltchanova, 2011, Annals of medicine.

Perinatal risk factors in young adult‐onset type 1 and type 2 diabetes – a population‐based case‐control study

P. Blomstedt, J. Tuomilehto, J. Eriksson, 2009, Acta obstetricia et gynecologica Scandinavica.

Association Between Type 2 Diabetes and Exposure to Persistent Organic Pollutants

P. Blomstedt, J. Eriksson, E. Kajantie, 2011, Diabetes Care.

Birth-weight and resting metabolic rate in adulthood — sex-specific differences

P. Blomstedt, J. Eriksson, E. Moltchanova, 2012, Annals of medicine.

The effect of birth order and parental age on the risk of type 1 and 2 diabetes among young adults

P. Blomstedt, J. Tuomilehto, J. Eriksson, 2007, Diabetologia.

Personality and Dietary Intake – Findings in the Helsinki Birth Cohort Study

P. Blomstedt, J. Eriksson, J. Lahti, 2013, PloS one.

Marked temporal increase in the incidence of type 1 and type 2 diabetes among young adults in Finland

P. Blomstedt, J. Tuomilehto, J. Eriksson, 2008, Diabetologia.

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

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

Distributed Bayesian matrix factorization with limited communication

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

Scalable Bayesian Non-linear Matrix Completion pdf

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

PCV72 EMPIRICAL EVALUATION OF THE PREDICTIVE PERFORMANCE OF CLASSIFICATION TOOLS IN CORONARY HEART DISEASE—P-COURSE, A NAIVE BAYES TOOL, OUTPERFORMS NOVEL LOGISTIC REGRESSION APPROACHES

J. Corander, P. Blomstedt, Jussi Lahtinen, 2007 .

Artificial Intelligence for chemical risk assessment

Andrew Worth, Tomi Peltola, John Paul Gosling, 2020, Computational toxicology.

Variance reduction for distributed stochastic gradient MCMC pdf

Samuel Kaski, Diego Mesquita, Paul Blomstedt, 2020, ArXiv.