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ORCIDGitta Kutyniok
Person information
- affiliation: LMU Munich, Department of Mathematics, Germany
- affiliation (former): TU Berlin, Institute of Mathematics, Germany
- affiliation (former): University of Osnabrück, Institute of Mathematics, Germany
- affiliation (former): Justus Liebig University of Giessen, Institute of Mathematics, Germany
- affiliation (PhD 2000): University of Paderborn, Department of Mathematics, Germany
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2020 – today
- 2024
[j42]Philipp Scholl, Maged Iskandar, Sebastian Wolf
, Jinoh Lee, Aras Bacho, Alexander Dietrich, Alin Albu-Schäffer, Gitta Kutyniok:
Learning-based adaption of robotic friction models. Robotics Comput. Integr. Manuf. 89: 102780 (2024)- [j41]Philipp Scholl, Maged Iskandar, Sebastian Wolf, Jinoh Lee, Aras Bacho, Alexander Dietrich, Alin Albu-Schäffer, Gitta Kutyniok:
Corrigendum to "Learning-based adaption of robotic friction models" [Robotics and Computer-Integrated Manufacturing Volume 89, October 2024]. Robotics Comput. Integr. Manuf. 89: 102783 (2024) - [j40]Yunseok Lee, Holger Boche, Gitta Kutyniok:
Computability of Optimizers. IEEE Trans. Inf. Theory 70(4): 2967-2983 (2024) - [c26]Holger Boche, Adalbert Fono, Gitta Kutyniok:
A Mathematical Framework for Computability Aspects of Algorithmic Transparency. ISIT 2024: 3089-3094 - [i88]Holger Boche, Adalbert Fono, Gitta Kutyniok:
Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement. CoRR abs/2401.10310 (2024) - [i87]Beatrice Lorenz, Aras Bacho, Gitta Kutyniok:
Error Estimation for Physics-informed Neural Networks Approximating Semilinear Wave Equations. CoRR abs/2402.07153 (2024) - [i86]Raffaele Paolino, Sohir Maskey, Pascal Welke, Gitta Kutyniok:
Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning. CoRR abs/2403.13749 (2024) - [i85]Sohir Maskey, Gitta Kutyniok, Ron Levie:
Generalization Bounds for Message Passing Networks on Mixture of Graphons. CoRR abs/2404.03473 (2024) - [i84]Holger Boche, Vít Fojtík, Adalbert Fono, Gitta Kutyniok:
Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization. CoRR abs/2408.06212 (2024) - [i83]Hillary Hauger, Philipp Scholl, Gitta Kutyniok:
Robust identifiability for symbolic recovery of differential equations. CoRR abs/2410.09938 (2024) - 2023
- [j39]Holger Boche, Adalbert Fono, Gitta Kutyniok:
Limitations of Deep Learning for Inverse Problems on Digital Hardware. IEEE Trans. Inf. Theory 69(12): 7887-7908 (2023) - [j38]Çagkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach. IEEE Trans. Wirel. Commun. 22(12): 9703-9717 (2023) - [c25]Stefan Kolek, Robert Windesheim, Héctor Andrade-Loarca, Gitta Kutyniok, Ron Levie:
Explaining Image Classifiers with Multiscale Directional Image Representation. CVPR 2023: 18600-18609 - [c24]Philipp Scholl, Aras Bacho, Holger Boche, Gitta Kutyniok:
The Uniqueness Problem of Physical Law Learning. ICASSP 2023: 1-5 - [c23]Çagkan Yapar, Fabian Jaensch, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
The First Pathloss Radio Map Prediction Challenge. ICASSP 2023: 1-2 - [c22]Duc Anh Nguyen, Ron Levie, Julian Lienen, Eyke Hüllermeier, Gitta Kutyniok:
Memorization-Dilation: Modeling Neural Collapse Under Noise. ICLR 2023 - [c21]Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie:
Unveiling the sampling density in non-uniform geometric graphs. ICLR 2023 - [c20]Çagkan Yapar, Fabian Jaensch, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
Overview of the Urban Wireless Localization Competition. MLSP 2023: 1-6 - [c19]Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok:
A Fractional Graph Laplacian Approach to Oversmoothing. NeurIPS 2023 - [c18]Mariia Seleznova, Dana Weitzner, Raja Giryes, Gitta Kutyniok, Hung-Hsu Chou:
Neural (Tangent Kernel) Collapse. NeurIPS 2023 - [c17]Silas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok:
Sumformer: Universal Approximation for Efficient Transformers. TAG-ML 2023: 72-86 - [i82]Yunseok Lee, Holger Boche, Gitta Kutyniok:
Computability of Optimizers. CoRR abs/2301.06148 (2023) - [i81]Christian Koke, Gitta Kutyniok:
Graph Scattering beyond Wavelet Shackles. CoRR abs/2301.11456 (2023) - [i80]Sohir Maskey, Raffaele Paolino, Aras Bacho, Gitta Kutyniok:
A Fractional Graph Laplacian Approach to Oversmoothing. CoRR abs/2305.13084 (2023) - [i79]Mariia Seleznova, Dana Weitzner, Raja Giryes, Gitta Kutyniok, Hung-Hsu Chou:
Neural (Tangent Kernel) Collapse. CoRR abs/2305.16427 (2023) - [i78]Hugo Tadashi M. Kussaba, Abdalla Swikir, Fan Wu, Anastasija Demerdjieva, Gitta Kutyniok, Sami Haddadin:
Learning optimal controllers: a dynamical motion primitive approach. CoRR abs/2306.06520 (2023) - [i77]Niklas Breustedt, Paolo Climaco, Jochen Garcke, Jan Hamaekers, Gitta Kutyniok, Dirk A. Lorenz, Rick Oerder, Chirag Varun Shukla:
On the Interplay of Subset Selection and Informed Graph Neural Networks. CoRR abs/2306.10066 (2023) - [i76]Aras Bacho, Holger Boche, Gitta Kutyniok:
Reliable AI: Does the Next Generation Require Quantum Computing? CoRR abs/2307.01301 (2023) - [i75]Silas Alberti, Niclas Dern, Laura Thesing, Gitta Kutyniok:
Sumformer: Universal Approximation for Efficient Transformers. CoRR abs/2307.02301 (2023) - [i74]Héctor Andrade-Loarca, Julius Hege, Aras Bacho, Gitta Kutyniok:
PoissonNet: Resolution-Agnostic 3D Shape Reconstruction using Fourier Neural Operators. CoRR abs/2308.01766 (2023) - [i73]Manjot Singh, Adalbert Fono, Gitta Kutyniok:
Expressivity of Spiking Neural Networks. CoRR abs/2308.08218 (2023) - [i72]Philipp Scholl, Katharina Bieker, Hillary Hauger, Gitta Kutyniok:
ParFam - Symbolic Regression Based on Continuous Global Optimization. CoRR abs/2310.05537 (2023) - [i71]Çagkan Yapar, Fabian Jaensch, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
The First Pathloss Radio Map Prediction Challenge. CoRR abs/2310.07658 (2023) - [i70]Philipp Scholl, Maged Iskandar, Sebastian Wolf, Jinoh Lee, Aras Bacho, Alexander Dietrich, Alin Albu-Schäffer, Gitta Kutyniok:
Learning-based adaption of robotic friction models. CoRR abs/2310.16688 (2023) - [i69]Gabriel Mukobi, Peter Chatain, Su Fong, Robert Windesheim, Gitta Kutyniok, Kush Bhatia, Silas Alberti:
SuperHF: Supervised Iterative Learning from Human Feedback. CoRR abs/2310.16763 (2023) - [i68]Stefan Kolek, Aditya Chattopadhyay, Kwan Ho Ryan Chan, Héctor Andrade-Loarca, Gitta Kutyniok, René Vidal:
Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. CoRR abs/2312.11548 (2023) - 2022
- [c16]Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok:
Cartoon Explanations of Image Classifiers. ECCV (12) 2022: 443-458 - [c15]Çagkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning. ICASSP 2022: 4063-4067 - [c14]Mariia Seleznova, Gitta Kutyniok:
Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization. ICML 2022: 19522-19560 - [c13]Christian Koke, Gitta Kutyniok:
Graph Scattering beyond Wavelet Shackles. NeurIPS 2022 - [c12]Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok:
Generalization Analysis of Message Passing Neural Networks on Large Random Graphs. NeurIPS 2022 - [c11]Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro:
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs. NeurIPS 2022 - [d1]Çagkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
Dataset of Pathloss and ToA Radio Maps with Localization Application. IEEE DataPort, 2022
- [i67]Mariia Seleznova, Gitta Kutyniok:
Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization. CoRR abs/2202.00553 (2022) - [i66]Sohir Maskey, Ron Levie, Yunseok Lee, Gitta Kutyniok:
Generalization Analysis of Message Passing Neural Networks on Large Random Graphs. CoRR abs/2202.00645 (2022) - [i65]Çagkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning. CoRR abs/2202.00738 (2022) - [i64]Holger Boche, Adalbert Fono, Gitta Kutyniok:
Limitations of Deep Learning for Inverse Problems on Digital Hardware. CoRR abs/2202.13490 (2022) - [i63]Gitta Kutyniok:
The Mathematics of Artificial Intelligence. CoRR abs/2203.08890 (2022) - [i62]Yangze Zhou, Gitta Kutyniok, Bruno Ribeiro:
OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs. CoRR abs/2205.15117 (2022) - [i61]Duc Anh Nguyen, Ron Levie, Julian Lienen, Gitta Kutyniok, Eyke Hüllermeier:
Memorization-Dilation: Modeling Neural Collapse Under Noise. CoRR abs/2206.05530 (2022) - [i60]Raffaele Paolino, Aleksandar Bojchevski, Stephan Günnemann, Gitta Kutyniok, Ron Levie:
Unveiling the Sampling Density in Non-Uniform Geometric Graphs. CoRR abs/2210.08219 (2022) - [i59]Philipp Scholl, Aras Bacho, Holger Boche, Gitta Kutyniok:
Well-definedness of Physical Law Learning: The Uniqueness Problem. CoRR abs/2210.08342 (2022) - [i58]Stefan Kolek, Robert Windesheim, Héctor Andrade-Loarca, Gitta Kutyniok, Ron Levie:
Explaining Image Classifiers with Multiscale Directional Image Representation. CoRR abs/2211.12857 (2022) - [i57]Aras Bacho, Holger Boche, Gitta Kutyniok:
Complexity Blowup for Solutions of the Laplace and the Diffusion Equation. CoRR abs/2212.00693 (2022) - [i56]Holger Boche, Adalbert Fono, Gitta Kutyniok:
Non-Computability of the Pseudoinverse on Digital Computers. CoRR abs/2212.02940 (2022) - [i55]Çagkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
Dataset of Pathloss and ToA Radio Maps With Localization Application. CoRR abs/2212.11777 (2022) - 2021
- [j37]Luis Oala, Cosmas Heiß, Jan MacDonald, Maximilian März, Gitta Kutyniok, Wojciech Samek:
Detecting failure modes in image reconstructions with interval neural network uncertainty. Int. J. Comput. Assist. Radiol. Surg. 16(12): 2089-2097 (2021) - [j36]Stephan Wäldchen, Jan MacDonald, Sascha Hauch, Gitta Kutyniok:
The Computational Complexity of Understanding Binary Classifier Decisions. J. Artif. Intell. Res. 70: 351-387 (2021) - [j35]Ron Levie, Wei Huang, Lorenzo Bucci, Michael M. Bronstein, Gitta Kutyniok:
Transferability of Spectral Graph Convolutional Neural Networks. J. Mach. Learn. Res. 22: 272:1-272:59 (2021) - [j34]Moritz Geist, Philipp Petersen, Mones Raslan, Reinhold Schneider, Gitta Kutyniok:
Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks. J. Sci. Comput. 88(1): 22 (2021) - [j33]Ali Hashemi, Chang Cai, Gitta Kutyniok, Klaus-Robert Müller, Srikantan S. Nagarajan, Stefan Haufe:
Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework. NeuroImage 239: 118309 (2021) - [j32]Ron Levie, Çagkan Yapar, Gitta Kutyniok, Giuseppe Caire:
RadioUNet: Fast Radio Map Estimation With Convolutional Neural Networks. IEEE Trans. Wirel. Commun. 20(6): 4001-4015 (2021) - [c10]Mariia Seleznova, Gitta Kutyniok:
Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory? MSML 2021: 868-895 - [i54]Julius Berner, Philipp Grohs, Gitta Kutyniok, Philipp Petersen:
The Modern Mathematics of Deep Learning. CoRR abs/2105.04026 (2021) - [i53]Çagkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
Real-time Outdoor Localization Using Radio Maps: A Deep Learning Approach. CoRR abs/2106.12556 (2021) - [i52]Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem, Philipp Petersen:
Deep Microlocal Reconstruction for Limited-Angle Tomography. CoRR abs/2108.05732 (2021) - [i51]Sohir Maskey, Ron Levie, Gitta Kutyniok:
Transferability of Graph Neural Networks: an Extended Graphon Approach. CoRR abs/2109.10096 (2021) - [i50]Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok:
Cartoon Explanations of Image Classifiers. CoRR abs/2110.03485 (2021) - [i49]Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok:
A Rate-Distortion Framework for Explaining Black-box Model Decisions. CoRR abs/2110.08252 (2021) - 2020
- [j31]Philipp Grohs, Gitta Kutyniok, Jackie Ma, Philipp Petersen, Mones Raslan:
Anisotropic multiscale systems on bounded domains. Adv. Comput. Math. 46(2): 39 (2020) - [j30]Joan Bruna, Eldad Haber, Gitta Kutyniok, Thomas Pock, René Vidal:
Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science. J. Math. Imaging Vis. 62(3): 277-278 (2020) - [c9]Ron Levie, Çagkan Yapar, Gitta Kutyniok, Giuseppe Caire:
Pathloss Prediction using Deep Learning with Applications to Cellular Optimization and Efficient D2D Link Scheduling. ICASSP 2020: 8678-8682 - [c8]Stefan Kolek, Duc Anh Nguyen, Ron Levie, Joan Bruna, Gitta Kutyniok:
A Rate-Distortion Framework for Explaining Black-Box Model Decisions. xxAI@ICML 2020: 91-115 - [i48]Alex Goeßmann, M. Götte, Ingo Roth, Ryan Sweke, Gitta Kutyniok, Jens Eisert:
Tensor network approaches for learning non-linear dynamical laws. CoRR abs/2002.12388 (2020) - [i47]Luis Oala, Cosmas Heiss, Jan MacDonald, Maximilian März, Wojciech Samek, Gitta Kutyniok:
Interval Neural Networks: Uncertainty Scores. CoRR abs/2003.11566 (2020) - [i46]Moritz Geist, Philipp Petersen, Mones Raslan, Reinhold Schneider, Gitta Kutyniok:
Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks. CoRR abs/2004.12131 (2020) - [i45]Héctor Andrade-Loarca, Gitta Kutyniok:
tfShearlab: The TensorFlow Digital Shearlet Transform for Deep Learning. CoRR abs/2006.04591 (2020) - [i44]Çagkan Yapar, Ron Levie, Gitta Kutyniok, Giuseppe Caire:
Real-time Localization Using Radio Maps. CoRR abs/2006.05397 (2020) - [i43]Alex Goeßmann, Gitta Kutyniok:
The Restricted Isometry of ReLU Networks: Generalization through Norm Concentration. CoRR abs/2007.00479 (2020) - [i42]Cosmas Heiß, Ron Levie, Cinjon Resnick, Gitta Kutyniok, Joan Bruna:
In-Distribution Interpretability for Challenging Modalities. CoRR abs/2007.00758 (2020) - [i41]Ingo Gühring, Mones Raslan, Gitta Kutyniok:
Expressivity of Deep Neural Networks. CoRR abs/2007.04759 (2020) - [i40]Ron Levie, Haim Avron, Gitta Kutyniok:
Quasi Monte Carlo Time-Frequency Analysis. CoRR abs/2011.02025 (2020) - [i39]Mariia Seleznova, Gitta Kutyniok:
Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory? CoRR abs/2012.04477 (2020)
2010 – 2019
- 2019
- [j29]Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem, Philipp Petersen:
Extraction of Digital Wavefront Sets Using Applied Harmonic Analysis and Deep Neural Networks. SIAM J. Imaging Sci. 12(4): 1936-1966 (2019) - [j28]Helmut Bölcskei, Philipp Grohs, Gitta Kutyniok, Philipp Petersen:
Optimal Approximation with Sparsely Connected Deep Neural Networks. SIAM J. Math. Data Sci. 1(1): 8-45 (2019) - [i38]Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem, Philipp Petersen:
Extraction of digital wavefront sets using applied harmonic analysis and deep neural networks. CoRR abs/1901.01388 (2019) - [i37]Dominik Alfke, Weston Baines, Jan Blechschmidt, Mauricio J. del Razo Sarmina, Amnon Drory, Dennis Elbrächter, Nando Farchmin, Matteo Gambara, Silke Glas, Philipp Grohs, Peter Hinz, Danijel Kivaranovic, Christian Kümmerle, Gitta Kutyniok, Sebastian Lunz, Jan MacDonald, Ryan Malthaner, Gregory Naisat, Ariel Neufeld, Philipp Christian Petersen, Rafael Reisenhofer, Jun-Da Sheng, Laura Thesing, Philipp Trunschke, Johannes von Lindheim, David Weber, Melanie Weber:
The Oracle of DLphi. CoRR abs/1901.05744 (2019) - [i36]Ron Levie, Elvin Isufi, Gitta Kutyniok:
On the Transferability of Spectral Graph Filters. CoRR abs/1901.10524 (2019) - [i35]Ingo Gühring, Gitta Kutyniok, Philipp Petersen:
Error bounds for approximations with deep ReLU neural networks in $W^{s, p}$ norms. CoRR abs/1902.07896 (2019) - [i34]Gitta Kutyniok, Philipp Petersen, Mones Raslan, Reinhold Schneider:
A Theoretical Analysis of Deep Neural Networks and Parametric PDEs. CoRR abs/1904.00377 (2019) - [i33]Rémi Gribonval, Gitta Kutyniok, Morten Nielsen, Felix Voigtländer:
Approximation spaces of deep neural networks. CoRR abs/1905.01208 (2019) - [i32]Stephan Wäldchen, Jan MacDonald, Sascha Hauch, Gitta Kutyniok:
The Computational Complexity of Understanding Network Decisions. CoRR abs/1905.09163 (2019) - [i31]Jan MacDonald, Stephan Wäldchen, Sascha Hauch, Gitta Kutyniok:
A Rate-Distortion Framework for Explaining Neural Network Decisions. CoRR abs/1905.11092 (2019) - [i30]Ron Levie, Michael M. Bronstein, Gitta Kutyniok:
Transferability of Spectral Graph Convolutional Neural Networks. CoRR abs/1907.12972 (2019) - [i29]Ron Levie, Çagkan Yapar, Gitta Kutyniok, Giuseppe Caire:
RadioUNet: Fast Radio Map Estimation with Convolutional Neural Networks. CoRR abs/1911.09002 (2019) - [i28]Héctor Andrade-Loarca, Gitta Kutyniok, Ozan Öktem:
Shearlets as Feature Extractor for Semantic Edge Detection: The Model-Based and Data-Driven Realm. CoRR abs/1911.12159 (2019) - 2018
- [j27]Wolfgang Dahmen, Gitta Kutyniok, Wang-Q Lim, Christoph Schwab, Gerrit Welper:
Adaptive anisotropic Petrov-Galerkin methods for first order transport equations. J. Comput. Appl. Math. 340: 191-220 (2018) - [j26]Gitta Kutyniok, Wang-Q Lim:
Optimal Compressive Imaging of Fourier Data. SIAM J. Imaging Sci. 11(1): 507-546 (2018) - [j25]Rafael Reisenhofer, Sebastian Bosse, Gitta Kutyniok, Thomas Wiegand:
A Haar wavelet-based perceptual similarity index for image quality assessment. Signal Process. Image Commun. 61: 33-43 (2018) - [c7]Gerhard Wunder, Ingo Roth, Mahdi Barzegar, Axel Flinth, Saeid Haghighatshoar, Giuseppe Caire, Gitta Kutyniok:
Hierarchical Sparse Channel Estimation for Massive MIMO. WSA 2018: 1-8 - [i27]Gerhard Wunder, Ingo Roth, Axel Flinth, Mahdi Barzegar, Saeid Haghighatshoar, Giuseppe Caire, Gitta Kutyniok:
Hierarchical Sparse Channel Estimation for Massive MIMO. CoRR abs/1803.10994 (2018) - [i26]Tatiana A. Bubba, Gitta Kutyniok, Matti Lassas, Maximilian März, Wojciech Samek, Samuli Siltanen, Vignesh Srinivasan:
Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography. CoRR abs/1811.04602 (2018) - 2017
- [j24]Tim O. F. Conrad, Martin Genzel, Nada Cvetkovic, Niklas Wulkow, Alexander B. Leichtle, Jan Vybíral, Gitta Kutyniok, Christof Schütte:
Sparse Proteomics Analysis - a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data. BMC Bioinform. 18(1): 160:1-160:20 (2017) - [j23]Jalal Fadili, Gitta Kutyniok, Gabriel Peyré, Gerlind Plonka-Hoch, Gabriele Steidl:
JMIV Special Issue Mathematics and Image Analysis. J. Math. Imaging Vis. 59(3): 371-372 (2017) - [i25]Jackie Ma, Maximilian März, Stephanie Funk, Jeanette Schulz-Menger, Gitta Kutyniok, Tobias Schaeffter, Christoph Kolbitsch:
Shearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting. CoRR abs/1705.00463 (2017) - [i24]Helmut Bölcskei, Philipp Grohs, Gitta Kutyniok, Philipp Petersen:
Optimal Approximation with Sparsely Connected Deep Neural Networks. CoRR abs/1705.01714 (2017) - [i23]Martin Genzel, Gitta Kutyniok, Maximilian März:
$\ell^1$-Analysis Minimization and Generalized (Co-)Sparsity: When Does Recovery Succeed? CoRR abs/1710.04952 (2017) - 2016
- [j22]Gitta Kutyniok, Wang-Q Lim, Rafael Reisenhofer:
ShearLab 3D: Faithful Digital Shearlet Transforms Based on Compactly Supported Shearlets. ACM Trans. Math. Softw. 42(1): 5:1-5:42 (2016) - [i22]Rafael Reisenhofer, Sebastian Bosse, Gitta Kutyniok, Thomas Wiegand:
A Haar Wavelet-Based Perceptual Similarity Index for Image Quality Assessment. CoRR abs/1607.06140 (2016) - [i21]Martin Genzel, Gitta Kutyniok:
A Mathematical Framework for Feature Selection from Real-World Data with Non-Linear Observations. CoRR abs/1608.08852 (2016) - 2015
- [j21]Jalal Fadili, Gitta Kutyniok, Gabriel Peyré, Gerlind Plonka-Hoch, Gabriele Steidl:
Guest Editorial: Mathematics and Image Analysis. J. Math. Imaging Vis. 52(3): 315-316 (2015) - [j20]Ben Adcock, Anders C. Hansen, Gitta Kutyniok, Jackie Ma:
Linear Stable Sampling Rate: Optimality of 2D Wavelet Reconstructions from Fourier Measurements. SIAM J. Math. Anal. 47(2): 1196-1233 (2015) - [j19]Haricharan Lakshman, Wang-Q Lim, Heiko Schwarz, Detlev Marpe, Gitta Kutyniok, Thomas Wiegand:
Image interpolation using shearlet based iterative refinement. Signal Process. Image Commun. 36: 83-94 (2015) - [j18]Xuemei Chen, Gitta Kutyniok, Kasso A. Okoudjou, Friedrich Philipp, Rongrong Wang:
Measures of Scalability. IEEE Trans. Inf. Theory 61(8): 4410-4423 (2015) - 2014
- [j17]Felix Krahmer, Gitta Kutyniok, Jakob Lemvig:
Sparse matrices in frame theory. Comput. Stat. 29(3): 547-568 (2014) - [j16]Philipp Grohs, Gitta Kutyniok:
Parabolic Molecules. Found. Comput. Math. 14(2): 299-337 (2014) - [j15]