27 citations · 31 across the 5 of their papers we have counts for
5 papers
Variational Inference Aided Estimation of Time Varying Channels
Benedikt Böck, Michael Baur, Valentina Rizzello +1
One way to improve the estimation of time varying channels is to incorporate knowledge of previous observations. In this context, Dynamical VAEs (DVAEs) build a promising deep lear…
Unsupervised Parameter Estimation using Model-based Decoder
Franz Weißer, Michael Baur, Wolfgang Utschick
In this work, we consider the use of a model-based decoder in combination with an unsupervised learning strategy for direction-of-arrival (DoA) estimation. Relying only on unlabele…
Model Order Selection with Variational Autoencoding
Michael Baur, Franz Weißer, Benedikt Böck +1
Classical methods for model order selection often fail in scenarios with low SNR or few snapshots. Deep learning-based methods are promising alternatives for such challenging situa…
Variational Autoencoder Leveraged MMSE Channel Estimation
Michael Baur, Benedikt Fesl, Michael Koller +1
We propose to utilize a variational autoencoder (VAE) for data-driven channel estimation. The underlying true and unknown channel distribution is modeled by the VAE as a conditiona…
CSI Clustering with Variational Autoencoding
Michael Baur, Michael Würth, Michael Koller +2
The model order of a wireless channel plays an important role for a variety of applications in communications engineering, e.g., it represents the number of resolvable incident wav…