5 citations · 6 across the 6 of their papers we have counts for
6 papers
StyleAutoEncoder for manipulating image attributes using pre-trained StyleGAN
Andrzej Bedychaj, Jacek Tabor, Marek Śmieja
Deep conditional generative models are excellent tools for creating high-quality images and editing their attributes. However, training modern generative models from scratch is ver…
Non-Gaussian Gaussian Processes for Few-Shot Regression
Marcin Sendera, Jacek Tabor, Aleksandra Nowak +5
Gaussian Processes (GPs) have been widely used in machine learning to model distributions over functions, with applications including multi-modal regression, time-series prediction…
On the relationship between disentanglement and multi-task learning
Łukasz Maziarka, Aleksandra Nowak, Maciej Wołczyk +1
One of the main arguments behind studying disentangled representations is the assumption that they can be easily reused in different tasks. At the same time finding a joint, adapta…
WICA: nonlinear weighted ICA
Andrzej Bedychaj, Przemysław Spurek, Aleksandra Nowak +1
Independent Component Analysis (ICA) aims to find a coordinate system in which the components of the data are independent. In this paper we construct a new nonlinear ICA model, cal…
Independent Component Analysis based on multiple data-weighting
Andrzej Bedychaj, Przemysław Spurek, Łukasz Struskim +1
Independent Component Analysis (ICA) - one of the basic tools in data analysis - aims to find a coordinate system in which the components of the data are independent. In this paper…
ICA based on Split Generalized Gaussian
P. Spurek, P. Rola, J. Tabor +1
Independent Component Analysis (ICA) - one of the basic tools in data analysis - aims to find a coordinate system in which the components of the data are independent. Most popular…