Alexander Fuchs — accepted AI-conference papers

2025

Avoiding Domain Drift and Constant Predictions with Diffusion Enhanced Vector-Quantized Autoencoders for Temperature Predictions

Nina Lampl, João Machado de Freitas, Alexander Fuchs, Benedikt Brezina, Michael Klitzsch, Franz Pernkopf

ICASSP 2025accepted

Accurate temperature prediction in rotary cement kilns is crucial for process stability and equipment longevity. However, the repeated application of the predicted values creates an error accumulation over the length of the forecast, causing a domain drift of the predictions. This issue is exacerbat…

Cited by 0 Source ↗Scholar ↗

2024

Data-Scarce Condition Modeling Requires Model-Based Prior Regularization

Nikolaus Mutsam, Alexander Fuchs, Fabio Ziegler, Franz Pernkopf

ICASSP 2024accepted

In the metallurgical industry, taking measurements during production can be infeasible or undesired, and only the terminated process can be measured. This poses problems for regression models, as the intermediate target values for a time series are hidden in the accumulated end-of-process measuremen…

Cited by 0 Source ↗Scholar ↗

2023

Self-Attention for Enhanced OAMP Detection in MIMO Systems

Alexander Fuchs, Christian Knoll, Nima N. Moghadam, Alexey Pak, Jinliang Huang, Erik Leitinger +1

ICASSP 2023accepted

Multiple-Input Multiple-Output (MIMO) systems are essential for wireless communications. Since classical algorithms for symbol detection in MIMO setups require large computational resources or provide poor results, data-driven algorithms are becoming more popular. Most of the proposed algorithms, ho…

Cited by 0 Source ↗Scholar ↗