8 citations · 9 across the 2 of their papers we have counts for
2 papers
cs.LG2021★ 8 cited
The Deep Generative Decoder: MAP estimation of representations improves modeling of single-cell RNA data
Viktoria Schuster, Anders Krogh
Learning low-dimensional representations of single-cell transcriptomics has become instrumental to its downstream analysis. The state of the art is currently represented by neural…
cs.LG2021★ 1 cited
A manifold learning perspective on representation learning: Learning decoder and representations without an encoder
Viktoria Schuster, Anders Krogh
Autoencoders are commonly used in representation learning. They consist of an encoder and a decoder, which provide a straightforward way to map n-dimensional data in input space to…