6 citations · 10 across the 4 of their papers we have counts for
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cs.LG2023★ 6 cited
Self-Supervised Siamese Autoencoders
Friederike Baier, Sebastian Mair, Samuel G. Fadel
In contrast to fully-supervised models, self-supervised representation learning only needs a fraction of data to be labeled and often achieves the same or even higher downstream pe…
cs.LG2023★ 1 cited
Archetypal Analysis++: Rethinking the Initialization Strategy
Sebastian Mair, Jens Sjölund
Archetypal analysis is a matrix factorization method with convexity constraints. Due to local minima, a good initialization is essential, but frequently used initialization methods…