activity
20112022
most citedBayesian Group Factor Analysis

69 citations · 129 across the 9 of their papers we have counts for

collaborators

9 papers

eess.IV2022★ 2 cited

A Generative Shape Compositional Framework to Synthesise Populations of Virtual Chimaeras

Haoran Dou, Seppo Virtanen, Nishant Ravikumar +1

Generating virtual populations of anatomy that capture sufficient variability while remaining plausible is essential for conducting in-silico trials of medical devices. However, no…

stat.AP2019★ 2 cited

Burglary in London: Insights from Statistical Heterogeneous Spatial Point Processes

Jan Povala, Seppo Virtanen, Mark Girolami

To obtain operational insights regarding the crime of burglary in London we consider the estimation of effects of covariates on the intensity of spatial point patterns. By taking i…

cs.LG2016

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

Seppo Virtanen, Homayun Afrabandpey, Samuel Kaski

A main goal of data visualization is to find, from among all the available alternatives, mappings to the 2D/3D display which are relevant to the user. Assuming user interaction dat…

stat.ML2014★ 1 cited

Group Factor Analysis

Arto Klami, Seppo Virtanen, Eemeli Leppäaho +1

Factor analysis provides linear factors that describe relationships between individual variables of a data set. We extend this classical formulation into linear factors that descri…

stat.ML2013★ 1 cited

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

Motivation: Analysis of relationships of drug structure to biological response is key to understanding off-target and unexpected drug effects, and for developing hypotheses on how…

cs.LG2012★ 34 cited

Factorized Multi-Modal Topic Model

Seppo Virtanen, Yangqing Jia, Arto Klami +1

Multi-modal data collections, such as corpora of paired images and text snippets, require analysis methods beyond single-view component and topic models. For continuous observation…