3 citations · 3 across the 3 of their papers we have counts for
3 papers
Self-Distilled Representation Learning for Time Series
Felix Pieper, Konstantin Ditschuneit, Martin Genzel +2
Self-supervised learning for time-series data holds potential similar to that recently unleashed in Natural Language Processing and Computer Vision. While most existing works in th…
Discrete Denoising Flows
Alexandra Lindt, Emiel Hoogeboom
Discrete flow-based models are a recently proposed class of generative models that learn invertible transformations for discrete random variables. Since they do not require data de…
Facial Expression Editing with Continuous Emotion Labels
Alexandra Lindt, Pablo Barros, Henrique Siqueira +1
Recently deep generative models have achieved impressive results in the field of automated facial expression editing. However, the approaches presented so far presume a discrete re…