Niklas Koep

According to our database, Niklas Koep authored at least 13 papers between 2015 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

Geomstats: A Python Package for Riemannian Geometry in Machine Learning.

Nina Miolane, Alice Le Brigant, Johan Mathe, Benjamin Hou, Nicolas Guigui, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Hadi Zaatiti, Hatem Hajri, Yann Cabanes, Thomas Gerald, Paul Chauchat, Christian Shewmake, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec

CoRR, 2020

Introduction to Geometric Learning in Python with Geomstats.

Nina Miolane, Nicolas Guigui, Hadi Zaatiti, Christian Shewmake, Hatem Hajri, Daniel Brooks, Alice Le Brigant, Johan Mathe, Benjamin Hou, Yann Thanwerdas, Stefan Heyder, Olivier Peltre, Niklas Koep, Yann Cabanes, Thomas Gerald, Paul Chauchat, Bernhard Kainz, Claire Donnat, Susan P. Holmes, Xavier Pennec

Proceedings of the 19th Python in Science Conference 2020 (SciPy 2020), Virtual Conference, July 6, 2020

Adversarial Risk Bounds through Sparsity based Compression.

Emilio Rafael Balda, Niklas Koep, Arash Behboodi, Rudolf Mathar

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Adversarial Risk Bounds for Neural Networks through Sparsity based Compression.

Emilio Rafael Balda, Arash Behboodi, Niklas Koep, Rudolf Mathar

CoRR, 2019

The Restricted Isometry Property of Block Diagonal Matrices for Group-Sparse Signal Recovery.

Niklas Koep, Arash Behboodi, Rudolf Mathar

CoRR, 2019

Efficient Implementation of Density Evolution for Punctured Polar Codes.

Christopher Schnelling, Markus Rothe, Niklas Koep, Rudolf Mathar, Anke Schmeink

IEEE Access, 2019

The Group Restricted Isometry Property for Subgaussian Block Diagonal Matrices.

Niklas Koep, Arash Behboodi, Rudolf Mathar

Proceedings of the IEEE International Symposium on Information Theory, 2019

Performance Analysis of One-bit Group-sparse Signal Reconstruction.

Niklas Koep, Arash Behboodi, Rudolf Mathar

Proceedings of the IEEE International Conference on Acoustics, 2019

2018

Block-Sparse Signal Recovery From Binary Measurements.

Niklas Koep, Rudolf Mathar

Proceedings of the 2018 IEEE Statistical Signal Processing Workshop, 2018

2017

Binary Iterative Hard Thresholding for Frequency-Sparse Signal Recovery.

Niklas Koep, Rudolf Mathar

Proceedings of the WSA 2017, 2017

2016

Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation.

James Townsend, Niklas Koep, Sebastian Weichwald

J. Mach. Learn. Res., 2016

Pymanopt: A Python Toolbox for Manifold Optimization using Automatic Differentiation.

James Townsend, Niklas Koep, Sebastian Weichwald

CoRR, 2016

2015

Noise-shaping for closed-loop Multi-Channel Linear Prediction.

Niklas Koep, Magnus Schaefer, Peter Vary

Proceedings of the 2015 IEEE International Conference on Acoustics, 2015