3 citations · 3 across the 3 of their papers we have counts for
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cs.LG2023
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…
cs.LG2021
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…