Wilson Bases for General Time-Frequency Lattices. - Gitta Kutyniok; Thomas Strohmer (SIAM J. Math. Anal., 2005)

Affine Density in Wavelet Analysis. - Gitta Kutyniok (Springer, 2007)

A generalization of Gram-Schmidt orthogonalization generating all Parseval frames. - Peter G. Casazza; Gitta Kutyniok (Adv. Comput. Math., 2007)

The Homogeneous Approximation Property for wavelet frames. - Christopher Heil; Gitta Kutyniok (J. Approx. Theory, 2007)

Analysis of 1 minimization in the Geometric Separation Problem. - David L. Donoho; Gitta Kutyniok (CISS, 2008)

Fusion frames and robust dimension reduction. - Ali Pezeshki; Gitta Kutyniok; A. Robert Calderbank (CISS, 2008)

08492 Abstracts Collection - Structured Decompositions and Efficient Algorithms. - Stephan Dahlke; Ingrid Daubechies; Michael Elad; Gitta Kutyniok; Gerd Teschke (Structured Decompositions and Efficient Algorithms, 2008)

08492 Executive Summary - Structured Decompositions and Efficient Algorithms. - Stephan Dahlke; Ingrid Daubechies; Michael Elad; Gitta Kutyniok; Gerd Teschke (Structured Decompositions and Efficient Algorithms, 2008)

The Uncertainty Principle Associated with the Continuous Shearlet Transform. - Stephan Dahlke; Gitta Kutyniok; Peter Maass; Chen Sagiv; Hans-Georg Stark; Gerd Teschke (Int. J. Wavelets Multiresolution Inf. Process., 2008)

A quantitative notion of redundancy for finite frames. - Bernhard G. Bodmann; Peter G. Casazza; Gitta Kutyniok (CoRR, 2009)

Adaptive Directional Subdivision Schemes and Shearlet Multiresolution Analysis. - Gitta Kutyniok; Tomas Sauer (SIAM J. Math. Anal., 2009)

Image Separation Using Wavelets and Shearlets. - Gitta Kutyniok; Wang-Q Lim (Curves and Surfaces, 2010)

Upper and lower redundancy of finite frames. - Bernhard G. Bodmann; Peter G. Casazza; Gitta Kutyniok (CISS, 2010)

Average case analysis of sparse recovery from combined fusion frame measurements. - Petros Boufounos; Gitta Kutyniok; Holger Rauhut (CISS, 2010)

Microlocal Analysis of the Geometric Separation Problem - David L. Donoho; Gitta Kutyniok (CoRR, 2010)

Sparse fusion frames: existence and construction. - A. Robert Calderbank; Peter G. Casazza; Andreas Heinecke; Gitta Kutyniok; Ali Pezeshki (Adv. Comput. Math., 2011)

Sparsity Equivalence of Anisotropic Decompositions - Gitta Kutyniok (CoRR, 2011)

Data Separation by Sparse Representations - Gitta Kutyniok (CoRR, 2011)

Shearlets and Optimally Sparse Approximations - Gitta Kutyniok; Jakob Lemvig; Wang-Q Lim (CoRR, 2011)

Digital Shearlet Transform - Gitta Kutyniok; Wang-Q Lim; Xiaosheng Zhuang (CoRR, 2011)

Sparse Representations and Efficient Sensing of Data (Dagstuhl Seminar 11051). - Stephan Dahlke; Michael Elad; Yonina C. Eldar; Gitta Kutyniok; Gerd Teschke (Dagstuhl Reports, 2011)

Compactly supported shearlets are optimally sparse. - Gitta Kutyniok; Wang-Q Lim (J. Approx. Theory, 2011)

Adaptive Multiresolution Analysis Structures and Shearlet Systems. - Bin Han 003; Gitta Kutyniok; Zuowei Shen (SIAM J. Numer. Anal., 2011)

Sparse Recovery From Combined Fusion Frame Measurements. - Petros Boufounos; Gitta Kutyniok; Holger Rauhut (IEEE Trans. Inf. Theory, 2011)

Optimally Sparse Frames. - Peter G. Casazza; Andreas Heinecke; Felix Krahmer; Gitta Kutyniok (IEEE Trans. Inf. Theory, 2011)

Introduction to compressed sensing. - Mark A. Davenport; Marco F. Duarte; Yonina C. Eldar; Gitta Kutyniok (Compressed Sensing, 2012)

Data separation by sparse representations. - Gitta Kutyniok (Compressed Sensing, 2012)

Compressed Sensing: Theory and Applications - Gitta Kutyniok (CoRR, 2012)

Scalable Frames - Gitta Kutyniok; Kasso A. Okoudjou; Friedrich Philipp; Elizabeth K. Tuley (CoRR, 2012)

Geometric Separation by Single-Pass Alternating Thresholding - Gitta Kutyniok (CoRR, 2012)

ShearLab: A Rational Design of a Digital Parabolic Scaling Algorithm. - Gitta Kutyniok; Morteza Shahram; Xiaosheng Zhuang (SIAM J. Imaging Sci., 2012)

Optimally Sparse Approximations of 3D Functions by Compactly Supported Shearlet Frames. - Gitta Kutyniok; Jakob Lemvig; Wang-Q Lim (SIAM J. Math. Anal., 2012)

Image interpolation using shearlet based sparsity priors. - Haricharan Lakshman; Wang-Q Lim; Heiko Schwarz; Detlev Marpe; Gitta Kutyniok; Thomas Wiegand 001 (ICIP, 2013)

Scalable Frames and Convex Geometry. - Gitta Kutyniok; Kasso A. Okoudjou; Friedrich Philipp (CoRR, 2013)

Clustered Sparsity and Separation of Cartoon and Texture. - Gitta Kutyniok (SIAM J. Imaging Sci., 2013)

Sparse matrices in frame theory. - Felix Krahmer; Gitta Kutyniok; Jakob Lemvig (Comput. Stat., 2014)

Parabolic Molecules. - Philipp Grohs; Gitta Kutyniok (Found. Comput. Math., 2014)

Analysis of Inpainting via Clustered Sparsity and Microlocal Analysis. - Emily J. King; Gitta Kutyniok; Xiaosheng Zhuang (J. Math. Imaging Vis., 2014)

Asymptotic Analysis of Inpainting via Universal Shearlet Systems. - Martin Genzel; Gitta Kutyniok (SIAM J. Imaging Sci., 2014)

Guest Editorial: Mathematics and Image Analysis. - Jalal Fadili; Gitta Kutyniok; Gabriel Peyré; Gerlind Plonka-Hoch; Gabriele Steidl (J. Math. Imaging Vis., 2015)

Linear Stable Sampling Rate: Optimality of 2D Wavelet Reconstructions from Fourier Measurements. - Ben Adcock; Anders C. Hansen; Gitta Kutyniok; Jackie Ma (SIAM J. Math. Anal., 2015)

Image interpolation using shearlet based iterative refinement. - Haricharan Lakshman; Wang-Q Lim; Heiko Schwarz; Detlev Marpe; Gitta Kutyniok; Thomas Wiegand 001 (Signal Process. Image Commun., 2015)

Measures of Scalability. - Xuemei Chen; Gitta Kutyniok; Kasso A. Okoudjou; Friedrich Philipp; Rongrong Wang (IEEE Trans. Inf. Theory, 2015)

A Mathematical Framework for Feature Selection from Real-World Data with Non-Linear Observations. - Martin Genzel; Gitta Kutyniok (CoRR, 2016)

ShearLab 3D: Faithful Digital Shearlet Transforms Based on Compactly Supported Shearlets. - Gitta Kutyniok; Wang-Q Lim; Rafael Reisenhofer (ACM Trans. Math. Softw., 2016)

Sparse Proteomics Analysis - a compressed sensing-based approach for feature selection and classification of high-dimensional proteomics mass spectrometry data. - Tim O. F. Conrad; Martin Genzel; Nada Cvetkovic; Niklas Wulkow; Alexander B. Leichtle; Jan Vybíral; Gitta Kutyniok; Christof Schütte (BMC Bioinform., 2017)

Shearlet-based compressed sensing for fast 3D cardiac MR imaging using iterative reweighting. - Jackie Ma; Maximilian März; Stephanie Funk; Jeanette Schulz-Menger; Gitta Kutyniok; Tobias Schaeffter; Christoph Kolbitsch (CoRR, 2017)

$ ell^1$-Analysis Minimization and Generalized (Co-)Sparsity: When Does Recovery Succeed? - Martin Genzel; Gitta Kutyniok; Maximilian März (CoRR, 2017)

JMIV Special Issue Mathematics and Image Analysis. - Jalal Fadili; Gitta Kutyniok; Gabriel Peyré; Gerlind Plonka-Hoch; Gabriele Steidl (J. Math. Imaging Vis., 2017)

Hierarchical Sparse Channel Estimation for Massive MIMO. - Gerhard Wunder; Ingo Roth; Mahdi Barzegar; Axel Flinth; Saeid Haghighatshoar; Giuseppe Caire; Gitta Kutyniok (WSA, 2018)

Learning The Invisible: A Hybrid Deep Learning-Shearlet Framework for Limited Angle Computed Tomography. - Tatiana A. Bubba; Gitta Kutyniok; Matti Lassas; Maximilian März; Wojciech Samek; Samuli Siltanen; Vignesh Srinivasan (CoRR, 2018)

Adaptive anisotropic Petrov-Galerkin methods for first order transport equations. - Wolfgang Dahmen; Gitta Kutyniok; Wang-Q Lim; Christoph Schwab; Gerrit Welper (J. Comput. Appl. Math., 2018)

Optimal Compressive Imaging of Fourier Data. - Gitta Kutyniok; Wang-Q Lim (SIAM J. Imaging Sci., 2018)

A Haar wavelet-based perceptual similarity index for image quality assessment. - Rafael Reisenhofer; Sebastian Bosse; Gitta Kutyniok; Thomas Wiegand 001 (Signal Process. Image Commun., 2018)

The Oracle of DLphi. - 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; et al. (CoRR, 2019)

On the Transferability of Spectral Graph Filters. - Ron Levie; Elvin Isufi; Gitta Kutyniok (CoRR, 2019)

Error bounds for approximations with deep ReLU neural networks in $W^{s, p}$ norms. - Ingo Gühring; Gitta Kutyniok; Philipp Petersen (CoRR, 2019)

A Theoretical Analysis of Deep Neural Networks and Parametric PDEs. - Gitta Kutyniok; Philipp Petersen; Mones Raslan; Reinhold Schneider (CoRR, 2019)

Approximation spaces of deep neural networks. - Rémi Gribonval; Gitta Kutyniok; Morten Nielsen 002; Felix Voigtländer (CoRR, 2019)

The Computational Complexity of Understanding Network Decisions. - Stephan Wäldchen; Jan MacDonald; Sascha Hauch; Gitta Kutyniok (CoRR, 2019)

A Rate-Distortion Framework for Explaining Neural Network Decisions. - Jan MacDonald; Stephan Wäldchen; Sascha Hauch; Gitta Kutyniok (CoRR, 2019)

Transferability of Spectral Graph Convolutional Neural Networks. - Ron Levie; Michael M. Bronstein; Gitta Kutyniok (CoRR, 2019)

Shearlets as Feature Extractor for Semantic Edge Detection: The Model-Based and Data-Driven Realm. - Héctor Andrade-Loarca; Gitta Kutyniok; Ozan Öktem (CoRR, 2019)

Extraction of Digital Wavefront Sets Using Applied Harmonic Analysis and Deep Neural Networks. - Héctor Andrade-Loarca; Gitta Kutyniok; Ozan Öktem; Philipp Petersen (SIAM J. Imaging Sci., 2019)

Optimal Approximation with Sparsely Connected Deep Neural Networks. - Helmut Bölcskei; Philipp Grohs; Gitta Kutyniok; Philipp Petersen (SIAM J. Math. Data Sci., 2019)

Pathloss Prediction using Deep Learning with Applications to Cellular Optimization and Efficient D2D Link Scheduling. - Ron Levie; Çagkan Yapar; Gitta Kutyniok; Giuseppe Caire (ICASSP, 2020)

A Rate-Distortion Framework for Explaining Black-Box Model Decisions. - Stefan Kolek; Duc Anh Nguyen; Ron Levie; Joan Bruna; Gitta Kutyniok (xxAI@ICML, 2020)

Anisotropic multiscale systems on bounded domains. - Philipp Grohs; Gitta Kutyniok; Jackie Ma; Philipp Petersen; Mones Raslan (Adv. Comput. Math., 2020)

Tensor network approaches for learning non-linear dynamical laws. - Alex Goeßmann; M. Götte; Ingo Roth; Ryan Sweke; Gitta Kutyniok; Jens Eisert (CoRR, 2020)

Interval Neural Networks: Uncertainty Scores. - Luis Oala; Cosmas Heiss; Jan MacDonald; Maximilian März; Wojciech Samek; Gitta Kutyniok (CoRR, 2020)

tfShearlab: The TensorFlow Digital Shearlet Transform for Deep Learning. - Héctor Andrade-Loarca; Gitta Kutyniok (CoRR, 2020)

Real-time Localization Using Radio Maps. - Çagkan Yapar; Ron Levie; Gitta Kutyniok; Giuseppe Caire (CoRR, 2020)

The Restricted Isometry of ReLU Networks: Generalization through Norm Concentration. - Alex Goeßmann; Gitta Kutyniok (CoRR, 2020)

In-Distribution Interpretability for Challenging Modalities. - Cosmas Heiß; Ron Levie; Cinjon Resnick; Gitta Kutyniok; Joan Bruna (CoRR, 2020)

Expressivity of Deep Neural Networks. - Ingo Gühring; Mones Raslan; Gitta Kutyniok (CoRR, 2020)

Quasi Monte Carlo Time-Frequency Analysis. - Ron Levie; Haim Avron; Gitta Kutyniok (CoRR, 2020)

Special Issue on the Mathematical Foundations of Deep Learning in Imaging Science. - Joan Bruna; Eldad Haber; Gitta Kutyniok; Thomas Pock; René Vidal (J. Math. Imaging Vis., 2020)

Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory? - Mariia Seleznova; Gitta Kutyniok (MSML, 2021)

Detecting failure modes in image reconstructions with interval neural network uncertainty. - Luis Oala; Cosmas Heiß; Jan MacDonald; Maximilian März; Gitta Kutyniok; Wojciech Samek (Int. J. Comput. Assist. Radiol. Surg., 2021)

The Modern Mathematics of Deep Learning. - Julius Berner; Philipp Grohs; Gitta Kutyniok; Philipp Petersen (CoRR, 2021)

Deep Microlocal Reconstruction for Limited-Angle Tomography. - Héctor Andrade-Loarca; Gitta Kutyniok; Ozan Öktem; Philipp Petersen (CoRR, 2021)

Transferability of Graph Neural Networks: an Extended Graphon Approach. - Sohir Maskey; Ron Levie; Gitta Kutyniok (CoRR, 2021)

The Computational Complexity of Understanding Binary Classifier Decisions. - Stephan Wäldchen; Jan MacDonald; Sascha Hauch; Gitta Kutyniok (J. Artif. Intell. Res., 2021)

Transferability of Spectral Graph Convolutional Neural Networks. - Ron Levie; Wei Huang; Lorenzo Bucci; Michael M. Bronstein; Gitta Kutyniok (J. Mach. Learn. Res., 2021)

Numerical Solution of the Parametric Diffusion Equation by Deep Neural Networks. - Moritz Geist; Philipp Petersen; Mones Raslan; Reinhold Schneider; Gitta Kutyniok (J. Sci. Comput., 2021)

Unification of sparse Bayesian learning algorithms for electromagnetic brain imaging with the majorization minimization framework. - Ali Hashemi 002; Chang Cai; Gitta Kutyniok; Klaus-Robert Müller; Srikantan S. Nagarajan; Stefan Haufe (NeuroImage, 2021)

RadioUNet: Fast Radio Map Estimation With Convolutional Neural Networks. - Ron Levie; Çagkan Yapar; Gitta Kutyniok; Giuseppe Caire (IEEE Trans. Wirel. Commun., 2021)

Cartoon Explanations of Image Classifiers. - Stefan Kolek; Duc Anh Nguyen; Ron Levie; Joan Bruna; Gitta Kutyniok (ECCV (12), 2022)

LocUNet: Fast Urban Positioning Using Radio Maps and Deep Learning. - Çagkan Yapar; Ron Levie; Gitta Kutyniok; Giuseppe Caire (ICASSP, 2022)

Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization. - Mariia Seleznova; Gitta Kutyniok (ICML, 2022)

Graph Scattering beyond Wavelet Shackles. - Christian Koke; Gitta Kutyniok (NeurIPS, 2022)

Generalization Analysis of Message Passing Neural Networks on Large Random Graphs. - Sohir Maskey; Ron Levie; Yunseok Lee; Gitta Kutyniok (NeurIPS, 2022)

OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs. - Yangze Zhou; Gitta Kutyniok; Bruno Ribeiro 001 (NeurIPS, 2022)

The Mathematics of Artificial Intelligence. - Gitta Kutyniok (CoRR, 2022)

Well-definedness of Physical Law Learning: The Uniqueness Problem. - Philipp Scholl 003; Aras Bacho; Holger Boche; Gitta Kutyniok (CoRR, 2022)

Complexity Blowup for Solutions of the Laplace and the Diffusion Equation. - Aras Bacho; Holger Boche; Gitta Kutyniok (CoRR, 2022)

Non-Computability of the Pseudoinverse on Digital Computers. - Holger Boche; Adalbert Fono; Gitta Kutyniok (CoRR, 2022)

Dataset of Pathloss and ToA Radio Maps With Localization Application. - Çagkan Yapar; Ron Levie; Gitta Kutyniok; Giuseppe Caire (CoRR, 2022)

Dataset of Pathloss and ToA Radio Maps with Localization Application. - Çagkan Yapar; Ron Levie; Gitta Kutyniok; Giuseppe Caire (IEEE DataPort, 2022)

Explaining Image Classifiers with Multiscale Directional Image Representation. - Stefan Kolek; Robert Windesheim; Héctor Andrade-Loarca; Gitta Kutyniok; Ron Levie (CVPR, 2023)

The Uniqueness Problem of Physical Law Learning. - Philipp Scholl 003; Aras Bacho; Holger Boche; Gitta Kutyniok (ICASSP, 2023)

The First Pathloss Radio Map Prediction Challenge. - Çagkan Yapar; Fabian Jaensch; Ron Levie; Gitta Kutyniok; Giuseppe Caire (ICASSP, 2023)

Memorization-Dilation: Modeling Neural Collapse Under Noise. - Duc Anh Nguyen; Ron Levie; Julian Lienen; Eyke Hüllermeier; Gitta Kutyniok (ICLR, 2023)

Unveiling the sampling density in non-uniform geometric graphs. - Raffaele Paolino; Aleksandar Bojchevski; Stephan Günnemann; Gitta Kutyniok; Ron Levie (ICLR, 2023)

Overview of the Urban Wireless Localization Competition. - Çagkan Yapar; Fabian Jaensch; Ron Levie; Gitta Kutyniok; Giuseppe Caire (MLSP, 2023)

A Fractional Graph Laplacian Approach to Oversmoothing. - Sohir Maskey; Raffaele Paolino; Aras Bacho; Gitta Kutyniok (NeurIPS, 2023)

Neural (Tangent Kernel) Collapse. - Mariia Seleznova; Dana Weitzner; Raja Giryes; Gitta Kutyniok; Hung-Hsu Chou (NeurIPS, 2023)

Sumformer: Universal Approximation for Efficient Transformers. - Silas Alberti; Niclas Dern; Laura Thesing; Gitta Kutyniok (TAG-ML, 2023)

Learning optimal controllers: a dynamical motion primitive approach. - Hugo Tadashi M. Kussaba; Abdalla Swikir; Fan Wu 015; Anastasija Demerdjieva; Gitta Kutyniok; Sami Haddadin (CoRR, 2023)

On the Interplay of Subset Selection and Informed Graph Neural Networks. - Niklas Breustedt; Paolo Climaco; Jochen Garcke; Jan Hamaekers; Gitta Kutyniok; Dirk A. Lorenz; Rick Oerder; Chirag Varun Shukla (CoRR, 2023)

Reliable AI: Does the Next Generation Require Quantum Computing? - Aras Bacho; Holger Boche; Gitta Kutyniok (CoRR, 2023)

PoissonNet: Resolution-Agnostic 3D Shape Reconstruction using Fourier Neural Operators. - Héctor Andrade-Loarca; Julius Hege; Aras Bacho; Gitta Kutyniok (CoRR, 2023)

Expressivity of Spiking Neural Networks. - Manjot Singh; Adalbert Fono; Gitta Kutyniok (CoRR, 2023)

ParFam - Symbolic Regression Based on Continuous Global Optimization. - Philipp Scholl 003; Katharina Bieker; Hillary Hauger; Gitta Kutyniok (CoRR, 2023)

SuperHF: Supervised Iterative Learning from Human Feedback. - Gabriel Mukobi; Peter Chatain; Su Fong; Robert Windesheim; Gitta Kutyniok; Kush Bhatia; Silas Alberti (CoRR, 2023)

Learning Interpretable Queries for Explainable Image Classification with Information Pursuit. - Stefan Kolek; Aditya Chattopadhyay; Kwan Ho Ryan Chan; Héctor Andrade-Loarca; Gitta Kutyniok; René Vidal (CoRR, 2023)

Limitations of Deep Learning for Inverse Problems on Digital Hardware. - Holger Boche; Adalbert Fono; Gitta Kutyniok (IEEE Trans. Inf. Theory, 2023)

Real-Time Outdoor Localization Using Radio Maps: A Deep Learning Approach. - Çagkan Yapar; Ron Levie; Gitta Kutyniok; Giuseppe Caire (IEEE Trans. Wirel. Commun., 2023)

Compositional Construction of Barrier Functions for Switched Impulsive Systems. - Katharina Bieker; Hugo T. M. Kussaba; Philipp Scholl 003; Jaesug Jung; Abdalla Swikir; Sami Haddadin; Gitta Kutyniok (CDC, 2024)

A Mathematical Framework for Computability Aspects of Algorithmic Transparency. - Holger Boche; Adalbert Fono; Gitta Kutyniok (ISIT, 2024)

Weisfeiler and Leman Go Loopy: A New Hierarchy for Graph Representational Learning. - Raffaele Paolino; Sohir Maskey; Pascal Welke; Gitta Kutyniok (NeurIPS, 2024)

Computing-Model and Computing-Hardware Selection for ICT Under Societal and Judicial Constraints. - Yannik N. Böck; Holger Boche; Frank H. P. Fitzek; Gitta Kutyniok (IEEE Access, 2024)

Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement. - Holger Boche; Adalbert Fono; Gitta Kutyniok (CoRR, 2024)

Error Estimation for Physics-informed Neural Networks Approximating Semilinear Wave Equations. - Beatrice Lorenz; Aras Bacho; Gitta Kutyniok (CoRR, 2024)

Generalization Bounds for Message Passing Networks on Mixture of Graphons. - Sohir Maskey; Gitta Kutyniok; Ron Levie (CoRR, 2024)

Computability of Classification and Deep Learning: From Theoretical Limits to Practical Feasibility through Quantization. - Holger Boche; Vít Fojtík; Adalbert Fono; Gitta Kutyniok (CoRR, 2024)

Learning-based adaption of robotic friction models. - Philipp Scholl 003; Maged Iskandar; Sebastian Wolf 001; Jinoh Lee; Aras Bacho; Alexander Dietrich; Alin Albu-Schäffer; Gitta Kutyniok (Robotics Comput. Integr. Manuf., 2024)

Corrigendum to "Learning-based adaption of robotic friction models" [Robotics and Computer-Integrated Manufacturing Volume 89, October 2024]. - Philipp Scholl 003; Maged Iskandar; Sebastian Wolf 001; Jinoh Lee; Aras Bacho; Alexander Dietrich; Alin Albu-Schäffer; Gitta Kutyniok (Robotics Comput. Integr. Manuf., 2024)

Computability of Optimizers. - Yunseok Lee; Holger Boche; Gitta Kutyniok (IEEE Trans. Inf. Theory, 2024)

Robust Identifiability for Symbolic Recovery of Differential Equations. - Hillary Hauger; Philipp Scholl 003; Gitta Kutyniok (ICASSP, 2025)

ParFam - (Neural Guided) Symbolic Regression via Continuous Global Optimization. - Philipp Scholl 003; Katharina Bieker; Hillary Hauger; Gitta Kutyniok (ICLR, 2025)

Probabilistic neural operators for functional uncertainty quantification. - Christopher Bülte; Philipp Scholl 003; Gitta Kutyniok (Trans. Mach. Learn. Res., 2025)

Sustainable AI: Mathematical Foundations of Spiking Neural Networks. - Adalbert Fono; Manjot Singh; Ernesto Araya; Philipp Christian Petersen; Holger Boche; Gitta Kutyniok (CoRR, 2025)

Graph Neural Networks for Enhancing Ensemble Forecasts of Extreme Rainfall. - Christopher Bülte; Sohir Maskey; Philipp Scholl 003; Jonas von Berg; Gitta Kutyniok (CoRR, 2025)

An Axiomatic Assessment of Entropy- and Variance-based Uncertainty Quantification in Regression. - Christopher Bülte; Yusuf Sale; Timo Löhr; Paul Hofman; Gitta Kutyniok; Eyke Hüllermeier (CoRR, 2025)

Graph Representational Learning: When Does More Expressivity Hurt Generalization? - Sohir Maskey; Raffaele Paolino; Fabian Jogl; Gitta Kutyniok; Johannes F. Lutzeyer (CoRR, 2025)

Interpretable Robotic Friction Learning via Symbolic Regression. - Philipp Scholl 003; Alexander Dietrich; Sebastian Wolf 001; Jinoh Lee; Alin Albu-Schäffer; Gitta Kutyniok; Maged Iskandar (CoRR, 2025)

GradPCA: Leveraging NTK Alignment for Reliable Out-of-Distribution Detection. - Mariia Seleznova; Hung-Hsu Chou; Claudio Mayrink Verdun; Gitta Kutyniok (CoRR, 2025)

Time to Spike? Understanding the Representational Power of Spiking Neural Networks in Discrete Time. - Duc Anh Nguyen; Ernesto Araya; Adalbert Fono; Gitta Kutyniok (CoRR, 2025)

Revisiting Glorot Initialization for Long-Range Linear Recurrences. - Noga Bar; Mariia Seleznova; Yotam Alexander; Gitta Kutyniok; Raja Giryes (CoRR, 2025)

Conflicting Biases at the Edge of Stability: Norm versus Sharpness Regularization. - Vít Fojtík; Maria Matveev; Hung-Hsu Chou; Gitta Kutyniok; Johannes Maly (CoRR, 2025)

RoboSwap: A GAN-driven Video Diffusion Framework For Unsupervised Robot Arm Swapping. - Yang Bai; Liudi Yang; George Eskandar; Fengyi Shen; Dong Chen; Mohammad Altillawi; Ziyuan Liu; Gitta Kutyniok (CoRR, 2025)

RoboEnvision: A Long-Horizon Video Generation Model for Multi-Task Robot Manipulation. - Liudi Yang; Yang Bai; George Eskandar; Fengyi Shen; Mohammad Altillawi; Dong Chen; Soumajit Majumder; Ziyuan Liu; Gitta Kutyniok; Abhinav Valada (CoRR, 2025)