Sara Taskinen

University of Jyväskylä — Finland

Computer Science · Physical Sciences

27h-index4.5kcitations110works2.52yr avg
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Research Topics

Blind Source Separation Techniques(35), Spectroscopy and Chemometric Analyses(31), Advanced Statistical Methods and Models(26), Statistical Methods and Bayesian Inference(11), Species Distribution and Climate Change(10)

Publications110 total

SpatialDownscaling: Methods for Spatial Downscaling Using Deep Learning
2026Open Access
gllvm: Generalized Linear Latent Variable Models. R package
Zenodo (CERN European Organization for Nuclear Research)·2026Open Access
Effect of smoking and smoking cessation intervention on postoperative complications of orthopedic and hand surgery: A single-center interventional study
Tobacco Prevention & Cessation·2026Open Access
Approximating prediction error variances and reliabilities in multiple-trait genomic prediction model using Monte Carlo sampling
2025Open Access
Time-aware UNet and super-resolution deep residual networks for spatial downscaling
arXiv (Cornell University)·2025Open Access
gllvm 2.0: fast fitting of advanced ordination methods and joint species distribution models
PeerJ·2025Open Access
Identifiable Autoregressive Variational Autoencoders for Nonlinear and Nonstationary Spatio-Temporal Blind Source Separation
Lecture notes in computer science·2025Open Access
Identifiable Autoregressive Variational Autoencoders for Nonlinear and Nonstationary Spatio-Temporal Blind Source Separation
arXiv (Cornell University)·2025Open Access
Comparing model-based unconstrained ordination methods in the analysis of high-dimensional compositional count data
Journal of Data Science Statistics and Visualisation·2025Open Access
Independent Component Analysis
International Encyclopedia of Statistical Science·2025· 2 cited
Restoration of forestry-drained boreal peatland ecosystems can effectively stop and reverse ecosystem degradation
Communications Earth & Environment·2024· 17 citedOpen Access
A Review of Generalized Linear Latent Variable Models and Related Computational Approaches
Wiley Interdisciplinary Reviews Computational Statistics·2024· 5 citedOpen Access
A comparison of joint species distribution models for percent cover data
Methods in Ecology and Evolution·2024· 5 citedOpen Access
Modelling multivariate spatio-temporal data with identifiable variational autoencoders
Neural Networks·2024· 2 citedOpen Access
Author response for "A Comparison of Joint Species Distribution Models for Percent Cover Data"
2024· 1 cited
Modelling multivariate spatio-temporal data with identifiable variational autoencoders
arXiv (Cornell University)·2024Open Access
Author response for "A Comparison of Joint Species Distribution Models for Percent Cover Data"
2024
A large-scale and long-term experiment to identify effectiveness of ecosystem restoration
2024· 4 citedOpen Access
A Comparison of Joint Species Distribution Models for Percent Cover Data
arXiv (Cornell University)·2024· 1 citedOpen Access
Nonlinear blind source separation exploiting spatial nonstationarity
Information Sciences·2024· 5 citedOpen Access
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Frequent Co-authors

Hannu Oja(20), Klaus Nordhausen(19), J.K. Miettinen(14), David I. Warton(12), Francis K. C. Hui(10), Jenni Niku(7), Seija Sirkiä(4), Otso Ovaskainen(3), Annaliisa Kankainen(3), Markus Matilainen(3), Joni Virta(3), F. Guillaume Blanchet(2), Robert B. O’Hara(2), Steven C. Walker(2), Sarianna Sipilä(2), Wesley Brooks(2), Riki Herliansyah(2), Esa Ollila(2), Katrin Illner(2), Fabian J. Theis(2)