An Impropriety Test Based on Block-Skew-Circulant Matrices. - Christoph Hellings; Michael Koller 001; Wolfgang Utschick (WSA, 2015)

Deformation Stability of Deep Convolutional Neural Networks on Sobolev Spaces. - Michael Koller 001; Johannes Grobmann; Ullrich J. Mönich; Holger Boche (ICASSP, 2018)

Machine Learning for Channel Estimation from Compressed Measurements. - Michael Koller 001; Christoph Hellings; Michael Knoedlseder; Thomas Wiese; David Neumann; Wolfgang Utschick (ISWCS, 2018)

Shift Invariance and Deformation Error Properties of Deep Convolutional Neural Networks Based on Wavelets. - Johannes Grobmann; Michael Koller 001; Ullrich J. Mönich; Holger Boche (SPAWC, 2018)

A Generalized Hard Thresholding Pursuit on Infinite Unions of Subspaces. - Michael Koller 001; Thomas Wiese; Wolfgang Utschick (WSA, 2018)

Learning-Based Channel Estimation for Various Antenna Array Configurations. - Michael Koller 001; Christoph Hellings; Wolfgang Utschick (SPAWC, 2019)

Evaluation of Neural-Network-Based Channel Estimators Using Measurement Data. - Christoph Hellings; Aymen Dehmani; Stefan Wesemann; Michael Koller 001; Wolfgang Utschick (WSA, 2019)

A Comparison of Prediction Algorithms and Nexting for Short Term Weather Forecasts. - Michael Koller 001; Johannes Feldmaier; Klaus Diepold (CoRR, 2019)

Learning a Low-Complexity Channel Estimator for One-Bit Quantization. - Benedikt Fesl; Michael Koller 001; Nurettin Turan; Wolfgang Utschick (ACSSC, 2020)

Towards Feature Validation in Time to Lane Change Classification using Deep Neural Networks. - Oliver De Candido; Michael Koller 001; Oliver Gallitz; Ron Melz; Michael Botsch; Wolfgang Utschick (ITSC, 2020)

Unsupervised Learning of Adaptive Codebooks for Deep Feedback Encoding in FDD Systems. - Nurettin Turan; Michael Koller 001; Samer Bazzi; Wen Xu 001; Wolfgang Utschick (ACSCC, 2021)

One-Bit Quantized Channel Prediction with Neural Networks. - Nurettin Turan; Michael Koller 001; Wolfgang Utschick (PIMRC, 2021)

A Low-Complexity MIMO Channel Estimator with Implicit Structure of a Convolutional Neural Network. - Benedikt Fesl; Nurettin Turan; Michael Koller 001; Wolfgang Utschick (SPAWC, 2021)

Centralized Learning of the Distributed Downlink Channel Estimators in FDD Systems using Uplink Data. - Benedikt Fesl; Nurettin Turan; Michael Koller 001; Michael Joham; Wolfgang Utschick (WSA, 2021)

On Distributional Invariances between Downlink and Uplink MIMO Channels. - Nurettin Turan; Michael Koller 001; Valentina Rizzello; Benedikt Fesl; Samer Bazzi; Wen Xu 001; Wolfgang Utschick (WSA, 2021)

Variational Autoencoder Leveraged MMSE Channel Estimation. - Michael Baur; Benedikt Fesl; Michael Koller 001; Wolfgang Utschick (IEEECONF, 2022)

Channel Estimation based on Gaussian Mixture Models with Structured Covariances. - Benedikt Fesl; Michael Joham; Sha Hu 001; Michael Koller 001; Nurettin Turan; Wolfgang Utschick (IEEECONF, 2022)

GMM-based Codebook Construction and Feedback Encoding in FDD Systems. - Nurettin Turan; Michael Koller 001; Benedikt Fesl; Samer Bazzi; Wen Xu 001; Wolfgang Utschick (IEEECONF, 2022)

CSI Clustering with Variational Autoencoding. - Michael Baur; Michael Würth; Michael Koller 001; Vlad-Costin Andrei; Wolfgang Utschick (ICASSP, 2022)

An Asymptotically Optimal Approximation of the Conditional Mean Channel Estimator Based on Gaussian Mixture Models. - Michael Koller 001; Benedikt Fesl; Nurettin Turan; Wolfgang Utschick (ICASSP, 2022)

Evaluation of a Gaussian Mixture Model-based Channel Estimator using Measurement Data. - Nurettin Turan; Benedikt Fesl; Moritz Grundei; Michael Koller 001; Wolfgang Utschick (ISWCS, 2022)

Learning a compressive sensing matrix with structural constraints via maximum mean discrepancy optimization. - Michael Koller 001; Wolfgang Utschick (Signal Process., 2022)

An Asymptotically MSE-Optimal Estimator Based on Gaussian Mixture Models. - Michael Koller 001; Benedikt Fesl; Nurettin Turan; Wolfgang Utschick (IEEE Trans. Signal Process., 2022)

On the Mean Square Error Optimal Estimator in One-Bit Quantized Systems. - Benedikt Fesl; Michael Koller 001; Wolfgang Utschick (IEEE Trans. Signal Process., 2023)

Encouraging Validatable Features in Machine Learning-Based Highly Automated Driving Functions. - Oliver De Candido; Michael Koller 001; Wolfgang Utschick (IEEE Trans. Intell. Veh., 2023)

A Versatile Low-Complexity Feedback Scheme for FDD Systems via Generative Modeling. - Nurettin Turan; Benedikt Fesl; Michael Koller 001; Michael Joham; Wolfgang Utschick (IEEE Trans. Wirel. Commun., 2024)