Niklas Koep

Publication Activity (10 Years)

Years Active: 2015-2020
Publications (10 Years): 13

Top Topics

Signal Recovery

Linear Prediction

Compressive Sensing

Top Venues

Publications

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
Introduction to Geometric Learning in Python with Geomstats. SciPy (2020)
Emilio Rafael Balda, Niklas Koep, Arash Behboodi, Rudolf Mathar
Adversarial Risk Bounds through Sparsity based Compression. AISTATS (2020)
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
Geomstats: A Python Package for Riemannian Geometry in Machine Learning. CoRR (2020)
Christopher Schnelling, Markus Rothe, Niklas Koep, Rudolf Mathar, Anke Schmeink
Efficient Implementation of Density Evolution for Punctured Polar Codes. IEEE Access 7 (2019)
Emilio Rafael Balda, Arash Behboodi, Niklas Koep, Rudolf Mathar
Adversarial Risk Bounds for Neural Networks through Sparsity based Compression. CoRR (2019)
Niklas Koep, Arash Behboodi, Rudolf Mathar
The Restricted Isometry Property of Block Diagonal Matrices for Group-Sparse Signal Recovery. CoRR (2019)
Niklas Koep, Arash Behboodi, Rudolf Mathar
The Group Restricted Isometry Property for Subgaussian Block Diagonal Matrices. ISIT (2019)
Niklas Koep, Arash Behboodi, Rudolf Mathar
Performance Analysis of One-bit Group-sparse Signal Reconstruction. ICASSP (2019)
Niklas Koep, Rudolf Mathar
Block-Sparse Signal Recovery From Binary Measurements. SSP (2018)
Niklas Koep, Rudolf Mathar
Binary Iterative Hard Thresholding for Frequency-Sparse Signal Recovery. WSA (2017)
James Townsend, Niklas Koep, Sebastian Weichwald
Pymanopt: A Python Toolbox for Manifold Optimization using Automatic Differentiation. CoRR (2016)
James Townsend, Niklas Koep, Sebastian Weichwald
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation. J. Mach. Learn. Res. 17 (2016)
Niklas Koep, Magnus Schaefer, Peter Vary
Noise-shaping for closed-loop Multi-Channel Linear Prediction. ICASSP (2015)