Neural Enhancement of Factor Graph-based Symbol Detection. - Luca Schmid; Laurent Schmalen (SPAWC, 2022)

Low-Complexity Near-Optimum Symbol Detection Based on Neural Enhancement of Factor Graphs. - Luca Schmid; Laurent Schmalen (IEEE Trans. Commun., 2022)

Structural Optimization of Factor Graphs for Symbol Detection via Continuous Clustering and Machine Learning. - Lukas Rapp; Luca Schmid; Andrej Rode; Laurent Schmalen (ICASSP, 2023)

Local Message Passing on Frustrated Systems. - Luca Schmid; Joshua Brenk; Laurent Schmalen (UAI, 2023)

Approximate Maximum a Posteriori Carrier Phase Estimator for Wiener Phase Noise Channels using Belief Propagation. - Shrinivas Chimmalgi; Andrej Rode; Luca Schmid; Laurent Schmalen (CoRR, 2023)

Optimization of Iterative Blind Detection Based on Expectation Maximization and Belief Propagation. - Luca Schmid; Tomer Raviv; Nir Shlezinger; Laurent Schmalen (IEEECONF, 2024)

Fast and Robust Expectation Propagation MIMO Detection via Preconditioned Conjugated Gradient. - Luca Schmid; Dominik Sulz; Laurent Schmalen (IEEECONF, 2024)

Blind Channel Estimation and Joint Symbol Detection with Data-Driven Factor Graphs. - Luca Schmid; Tomer Raviv; Nir Shlezinger; Laurent Schmalen (CoRR, 2024)

Uncertainty Propagation in the Fast Fourier Transform. - Luca Schmid; Charlotte Muth; Laurent Schmalen (CoRR, 2025)