A Bayesian Predictive Model for Clustering Data of Mixed Discrete and Continuous Type. - Paul Blomstedt; Jing Tang 002; Jie Xiong; Christian Granlund; Jukka Corander (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

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

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

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

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

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

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)

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

Expectation Propagation as a Way of Life: A Framework for Bayesian Inference on Partitioned Data. - Aki Vehtari; Andrew Gelman; Tuomas Sivula; Pasi Jylänki; Dustin Tran; Swupnil Sahai; Paul Blomstedt; John P. Cunningham; David Schiminovich; Christian P. Robert (J. Mach. Learn. Res., 2020)

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