Pymanopt: A python toolbox for optimization on manifolds using automatic differentiation J Townsend, N Koep, S Weichwald The Journal of Machine Learning Research 17 (1), 4755-4759, 2016 | 315 | 2016 |

Geomstats: a Python package for Riemannian geometry in machine learning N Miolane, N Guigui, A Le Brigant, J Mathe, B Hou, Y Thanwerdas, ... Journal of Machine Learning Research 21 (223), 1-9, 2020 | 99 | 2020 |

Compressed sensing applied to spherical near-field to far-field transformation R Cornelius, D Heberling, N Koep, A Behboodi, R Mathar 2016 10th European Conference on Antennas and Propagation (EuCAP), 1-4, 2016 | 52 | 2016 |

Introduction to geometric learning in python with geomstats N Miolane, N Guigui, H Zaatiti, C Shewmake, H Hajri, D Brooks, ... SciPy 2020-19th Python in Science Conference, 48-57, 2020 | 14 | 2020 |

Adversarial risk bounds for neural networks through sparsity based compression ER Balda, A Behboodi, N Koep, R Mathar arXiv preprint arXiv:1906.00698, 2019 | 9 | 2019 |

Block-sparse signal recovery from binary measurements N Koep, R Mathar 2018 IEEE Statistical Signal Processing Workshop (SSP), 293-297, 2018 | 8 | 2018 |

The restricted isometry property of block diagonal matrices for group-sparse signal recovery N Koep, A Behboodi, R Mathar Applied and Computational Harmonic Analysis 60, 333-367, 2022 | 7 | 2022 |

An introduction to compressed sensing N Koep, A Behboodi, R Mathar Compressed Sensing and Its Applications: Third International MATHEON …, 2019 | 7 | 2019 |

Binary iterative hard thresholding for frequency-sparse signal recovery N Koep, R Mathar WSA 2017; 21th International ITG Workshop on Smart Antennas, 1-7, 2017 | 7 | 2017 |

Efficient implementation of density evolution for punctured polar codes C Schnelling, M Rothe, N Koep, R Mathar, A Schmeink IEEE Access 7, 105909-105921, 2019 | 5 | 2019 |

Geomstats: A Python Package for Riemannian Geometry in Machine Learning. 2020 N Miolane, AL Brigant, J Mathe, B Hou, N Guigui, Y Thanwerdas, ... arXiv preprint arXiv:2004.04667, 0 | 5 | |

Performance analysis of one-bit group-sparse signal reconstruction N Koep, A Behboodi, R Mathar ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019 | 3 | 2019 |

Pymanopt: A Python Toolbox for manifold optimization using automatic differentiation N Koep, S Weichwald arXiv preprint arXiv 1603, 2016 | 2 | 2016 |

Adversarial Risk Bounds through Sparsity based Compression E Balda, N Koep, A Behboodi, R Mathar International Conference on Artificial Intelligence and Statistics, 3816-3825, 2020 | 1 | 2020 |

The group restricted isometry property for subgaussian block diagonal matrices N Koep, A Behboodi, R Mathar 2019 IEEE International Symposium on Information Theory (ISIT), 2694-2698, 2019 | 1 | 2019 |

Quantized compressive sampling for structured signal estimation N Koep Dissertation, RWTH Aachen University, 2019, 2019 | | 2019 |

Noise-shaping for closed-loop Multi-Channel Linear Prediction N Koep, M Schäfer, P Vary 2015 IEEE International Conference on Acoustics, Speech and Signal …, 2015 | | 2015 |

Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation S Weichwald, J Townsend, N Koep | | |