33 citations · 41 across the 4 of their papers we have counts for
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cs.LG2022★ 2 cited
Gradient-Based Learning of Discrete Structured Measurement Operators for Signal Recovery
Jonathan Sauder, Martin Genzel, Peter Jung
Countless signal processing applications include the reconstruction of signals from few indirect linear measurements. The design of effective measurement operators is typically con…
cs.LG2020★ 1 cited
Neurally Augmented ALISTA
Freya Behrens, Jonathan Sauder, Peter Jung
It is well-established that many iterative sparse reconstruction algorithms can be unrolled to yield a learnable neural network for improved empirical performance. A prime example…
cs.LG2019★ 33 cited
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space
Jonathan Sauder, Bjarne Sievers
Point clouds provide a flexible and natural representation usable in countless applications such as robotics or self-driving cars. Recently, deep neural networks operating on raw p…