2 papers
cs.IT2026
A Tensor-Train Framework for Bayesian Inference in High-Dimensional Systems: Applications to MIMO Detection and Channel Decoding
Luca Schmid, Dominik Sulz, Shrinivas Chimmalgi +1
Bayesian inference in high-dimensional discrete-input additive noise models is a fundamental challenge in communication systems, as the support of the required joint a posteriori p…
cs.LG2025
Uncertainty Propagation in the Fast Fourier Transform
Luca Schmid, Charlotte Muth, Laurent Schmalen
We address the problem of uncertainty propagation in the discrete Fourier transform by modeling the fast Fourier transform as a factor graph. Building on this representation, we pr…