Bavarian AI Chair for Mathematical Foundations of Artificial Intelligence
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Refereed Conference Proceedings

2023

  • C. Kümmerle, J. Maly. Recovering Simultaneously Structured Data via Non-Convex Iteratively Reweighted Least Squares. NeurIPS 2023 (arXiv:2306.04961)
  • S. Maskey*, R. Paolino*, A. Bacho, G. Kutyniok. A Fractional Graph Laplacian Approach to Oversmoothing. NeurIPS 2023 (arXiv:2305.13084)
  • G. Kaissis, A. Ziller, S. Kolek, A. Riess, D. Rückert. Optimal Privacy Guarantees Against Sub-Optimal Adversaries in Differentially Private Machine Learning. NeurIPS 2023 [pdf]
  • M. Seleznove, D. Weitzner, R. Giryes, G. Kutyniok, H. Chou. Neural (Tangent Kernel) Collapse. NeurIPS 2023 (arXiv:2305.16427)
  • P. Scholl, A. Bacho, H. Boche and G. Kutyniok. "The Uniqueness Problem of Physical Law Learning". IEEE ICASSP. 2023 (arXiv:2210.08342)
  • S. Kolek, R. Windesheim, H. Andrade Loarca, G. Kutyniok, R. Levie. Explaining Image Classifiers with Multiscale Directional Image Representation. CVPR 2023 (arXiv:2211.12857)
  • R. Paolino, A. Bojchevski, S. Günnemann, G. Kutyniok, R. Levie. Unveiling the sampling density in non-uniform geometric graphs. ICLR 2023 (arXiv:2210.08219)
  • D. Nguyen, R. Levie, J. Lienen, G. Kutyniok, E. Hüllermeier. Memorization-Dilation: Modeling Neural Collapse Under Noise. ICLR 2023 (arXiv:2206.05530)
  • S. Alberti, N. Dern, L. Thesing, and G. Kutyniok. Sumformer: Universal approximation for efficient transformers. Topological, Algebraic and Geometric Learning Workshops 2023, pp. 72-86. PMLR, 2023 (pdf)

2022

  • C. Koke and G. Kutyniok. Graph Scattering beyond Wavelet Shackles. NeurIPS 2022 (arXiv:2301.11456).
  • V. Giunchiglia*, C. Varun Shukla*, G. Gonzalez, C. Agarwal. Proceedings of the First Learning on Graphs Conference (LoG 2022). (pdf)
  • S. Maskey, Y. Lee, R. Levie, and G. Kutyniok. Generalization Analysis of Message Passing Neural Networks on Large Random Graphs. NeurIPS 2022 (arXiv:2202.00645)
  • Y. Zhou, G. Kutyniok, B. Ribeiro. OOD Link Prediction Generalization Capabilities of Message-Passing GNNs in Larger Test Graphs, NeurIPS 2022 (arXiv:2205.15117)
  • P. Scholl, F. Dietrich, C. Otte, and S. Udluft. Safe Policy Improvement Approaches on Discrete Markov Decision Processes. ICAART 2022  (arXiv:2201.12175). 
  • C. Yaper, R. Levie, G. Kutyniok, and G. Caire. LOCUNET: Fast Urban Positioning Using Radio Maps and Deep Learning, ICASS (arXiv:2202.00738)
  • M. Seleznova and G. Kutyniok. Neural Tangent Kernel Beyond the Infinite-Width Limit: Effects of Depth and Initialization. ICML 2022 (arXiv:2202.00553).
  • S. Kolek, D. Nguyen, R. Levie, J. Bruna, G. Kutyniok. Cartoon Explanations of Image Classifiers. ECCV 2022 (oral) (arXiv:2110.03485).
  • G. Kutyniok. An Introduction to the Mathematics of Deep Learning. In: Proceedings of th 8th European Congress of Mathematics (8ECM) (pdf).

2021

  • M. Seleznova, G.  Kutyniok. Analyzing Finite Neural Networks: Can We Trust Neural Tangent Kernel Theory? Mathematical and Scientific Machine Learning Conference, 2021. (arXiv:2012.04477)

2020

  • A. Goeßmann, M. Götte, I. Roth, R. Sweke, G. Kutyniok, and J. Eisert. Tensor Network Approaches for Data-Driven Identification of Non-Linear Dynamical Laws. NeurIPS, Quantum Tensor Networks in Machine Learning, 2020. (arXiv:2002.12388)
  • C. Heiß, R. Levie, C. Resnick, G. Kutyniok, and J. Bruna. In-Distribution Interpretability for Challenging Modalities. ICML, Interpretability for Scientific Discovery, 2020. (arXiv:2007.00758)
  • J. Macdonald, S. Wäldchen, S. Hauch, and G. Kutyniok. Explaining Neural Network Decisions Is Hard. ICML, Extending Explainable AI Beyond Deep Models and Classifiers, 2020.
  • R. Levie, C. Yapar, G. Kutyniok, and G. Caire. Pathloss Prediction using Deep Learning with Applications to Cellular Optimization and Efficient D2D Link Scheduling. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020. [pdf]
  • L. Oala, C. Heiss, J. Macdonald, M. März, G. Kutyniok, and W. Samek. Detecting Failure Modes in Image Reconstruction with Interval Neural Network Uncertainty. ICML, Uncertainty & Robustness in Deep Learning, 2020 (Spotlight Paper). (arXiv:2003.11566)

2019

  • R. Levie, E. Isufi, and G. Kutyniok. On the Transferability of Spectral Graph Filters. SampTA’19 (Bordeaux, France, 2019), J.-F. Aujol, A. Hartmann, P. Jaming, and K. Kellay, eds., Proc. 2019. (arXiv:1901.10524)
  • R. Levie, W. Huang, L. Bucci, M. Bronstein, and G. Kutyniok. Transferability of Spectral Graph Convolutional Neural Networks. NeurIPS, Graph Representation Learning, 2019. (arXiv:1907.12972)

2018

  • G. Wunder, I. Roth, M. Barzegar, A. Flinth, S. Haghighatshoar, G. Caire, and G. Kutyniok. Hierarchical Sparse Channel Estimation for Massive MIMO. 22nd International ITG Workshop on Smart Antennas (WSA 2018), March 14-16, 2018 in Bochum, Germany. [pdf]

2017

  • H. Bölcskei, P. Grohs, G. Kutyniok, and P. Petersen. Memory-Optimal Neural Network Approximation. Wavelets and Sparsity XVII (San Diego, CA, 2017), 103940Q, SPIE Proc. 10394, Y. M. Lu, D. Van De Ville, and M. Papadakis, eds., SPIE, Bellingham, WA, 2017. [pdf]
  • S. Keiper, G. Kutyniok, D. Lee, and G. Pfander. Reconstruction of finite-valued sparse signals. Wavelets and Sparsity XVII (San Diego, CA, 2017), 1039415, SPIE Proc. 10394, Y. M. Lu, D. Van De Ville, and M. Papadakis, eds., SPIE, Bellingham, WA, 2017. [pdf]

2016

  • D. Mücke-Herzberg, P. Abellan, M. Sarahan, I. Godfrey, Z. Saghi, R. Leary, A. Stevens, J. Ma, G. Kutyniok, F. Azough, R. Freer, P. Midgley, N. Browning, and Q. Ramasse. A Compressive Sensing based acquisition design for quantitative ultra-low dose high-resolution imaging and spectroscopy in the STEM. Proceedings of the European Microscopy Congress, 2016.

2015

  • G. Kutyniok, V. Paternostro, and F. Philipp. Perturbations of Fusion Frames and the Effect on Their Canonical Dual. Wavelets and Sparsity XVI (San Diego, CA, 2015), 95970S–95977S, SPIE Proc. 9597, M. Papadakis, D. Van De Ville, V.K. Goyal, eds., SPIE, Bellingham, WA, 2015. [pdf]

2014

  • S. Keiper, G.Kutyniok, P. Grohs, and M. Schäfer. Parabolic Molecules: Curvelets, Shearlets, and Beyond. In Approximation Theory XIV (San Antonio, TX, 2013), L.L. Schumaker and G. E. Fasshauer, eds., Springer Proc. Math. (2014), 141–172. [link]

2013

  • G. Kutyniok, K. Okoudjou and F. Philipp. Perfect Preconditioning of Frames by a Diagonal Operator. 10th International Conference on Sampling Theory and Applications (Bremen, Germany, 2013), 85–88, Eurasip, 2013. [link]
  • H. Boche, M. Guillemard, G. Kutyniok, and F. Philipp. Signal Analysis with Frame Theory and Persistent Homology. 10th International Conference on Sampling Theory and Applications (Bremen, Germany, 2013), 309–331, Eurasip, 2013. [link]
  • F. Krahmer, G. Kutyniok, and J. Lemvig. Spectral properties of dual frames. 10th International Conference on Sampling Theory and Applications (Bremen, Germany, 2013), 493–496, Eurasip, 2013. [link]
  • H. Lakshman, W.-Q Lim, H. Schwarz, D. Marpe, G. Kutyniok, and T. Wiegand. Image Interpolation using Shearlet Based Sparsity Priors. IEEE International Conference on Image Processing (ICIP 2013), 655–659, IEEE, 2013. [link]
  • E. King, G.Kutyniok, and W.-Q Lim. Image Inpainting: Theoretical Analysis and Comparison of Algorithms. Wavelets and Sparsity XV (San Diego, CA, 2013), 885802-1–885802- SPIE Proc. 8858, M. Papadakis, D. Van De Ville, V.K. Goyal, eds., SPIE, Bellingham, WA, 2013. [link]
  • S. Keiper, G.Kutyniok, P. Grohs, and M. Schäfer. α-Molecules: Curvelets, Shearlets, Ridgelets, and Beyond. Wavelets and Sparsity XV (San Diego, CA, 2013), 885804-1– 885804-12, SPIE Proc. 8858, M. Papadakis, D. Van De Ville, V.K. Goyal, eds., SPIE, Bellingham, WA, 2013. [link]
  • G. Kutyniok, K. A. Okoudjou, and F. Philipp. Preconditioning of Frames. Wavelets and Sparsity XV (San Diego, CA, 2013), G88580-1–G88580-8, SPIE Proc. 8858, M. Papadakis, D. Van De Ville, V.K. Goyal, eds., SPIE, Bellingham, WA, 2013. [link]
  • H. Boche, M. Guillemard, G. Kutyniok, and F. Philipp. Signal Recovery from Thresholded Frame Measurements. Wavelets and Sparsity XV (San Diego, CA, 2013), D88580- 1–D88580-7, SPIE Proc. 8858, M. Papadakis, D. Van De Ville, V.K. Goyal, eds., SPIE, Bellingham, WA, 2013. [link]
  • G. Kutyniok, K. Okoudjou, and F. Philipp. Scalable Frames and Convex Geometry. In Spectra of Wavelets, Tilings, and Frames (Boulder, CO, 2012), V. Furst, K. Kornelsen, and E. Weber, eds., Contemp. Math. 345, Amer. Math. Soc., Providence, RI (2013), 19–32. 

 2012

  • G. Kutyniok and W.-Q Lim. Shearlets on Bounded Domains. Approximation Theory XIII (San Antonio, TX, 2010), Springer Proc. Math. 13, 187–206, Springer, 2012. [link]
  • G. Kutyniok, J. Lemvig, and W.-Q Lim. Compactly Supported Shearlets. Approximation Theory XIII (San Antonio, TX, 2010), Springer Proc. Math. 13, 163–186, Springer, 2012. [link]

2011

  • D. L. Donoho, G. Kutyniok, M. Shahram, and X. Zhuang. A Rational Design of a Digital Shearlet Transform. SampTA’11 (Singapore, 2011), Proc., 2011. [link]
  • P. G. Casazza, A. Heinecke, and G. Kutyniok. Optimally Sparse Fusion Frames: Existence and Construction. SampTA’11 (Singapore, 2011), Proc., 2011. [link]
  • B. G. Bodmann, P. G. Casazza, and G. Kutyniok. A Quantitative Notion of Redundancy and its Applications. SampTA’11 (Singapore, 2011), Proc., 2011. [link]
  • G. Kutyniok, J. Lemvig, and W.-Q Lim. Optimally Sparse Approximations of Multivariate Functions Using Compactly Supported Shearlet Frames. SampTA’11 (Singapore, 2011), Proc., 2011. [link]
  • G. Kutyniok and W.-Q Lim. Image Separation using Wavelets and Shearlets. Curves and Surfaces (Avignon, France, 2010), Lecture Notes in Computer Science, 416–430, Springer, 2010. [link]
  • E. J. King, G. Kutyniok, and X. Zhuang. Analysis of Data Separation and Recovery Problems using Clustered Sparsity. Wavelets and Sparsity XIV (San Diego, CA, 2009), 813818-1–813818-11, SPIE Proc. 8138, M. Papadakis, D. Van De Ville, V.K. Goyal, eds., SPIE, Bellingham, WA, 2011. [link]
  • B. G. Bodmann, G. Kutyniok, and X. Zhuang. Coarse Quantization with the Fast Digital Shearlet Transform. Wavelets and Sparsity XIV (San Diego, CA, 2009), 8138OZ-1– 8138OZ-10, SPIE Proc. 8138, M. Papadakis, D. Van De Ville, V.K. Goyal, eds., SPIE, Bellingham, WA, 2011. [link]

2010

  • B. Boufounos, G. Kutyniok, and H. Rauhut. Average Case Analysis of Sparse Recovery from Combined Fusion Frame Measurements. 43nd Annual Conference on Information Sciences and Systems (CISS) (Princeton University, NJ, 2010), 2010. [link]
  • B. G. Bodmann, P. G. Casazza, and G. Kutyniok. Upper and Lower Redundancy of Finite Frames. 43nd Annual Conference on Information Sciences and Systems (CISS) (Princeton University, NJ, 2010), 2010. [link]

2009

  •  D. L. Donoho and G. Kutyniok. Geometric Separation using a Wavelet-Shearlet Dictionary. SampTA’09 (Marseille, France, 2009), B. Torresani and L. Fesquet, eds., Proc., 2009. [link]
  • B. G. Bodmann, P. G. Casazza, G. Kutyniok, and S. Senger. Error Correction for Erasures of Quantized Frame Coefficients. SampTA’09 (Marseille, France, 2009), B. Torresani and L. Fesquet, eds., Proc., 2009. [link]
  • B. G. Bodmann, G. Kutyniok and A. Pezeshki. Erasure-Proof Coding with Fusion Frames. SampTA’09 (Marseille, France, 2009), B. Torresani and L. Fesquet, eds., Proc., 2009. [link]
  • R. Calderbank, P. G. Casazza, A. Heinecke, G. Kutyniok, and A. Pezeshki. Constructing Fusion Frames with Desired Parameters. Wavelets XIII (San Diego, CA, 2009), 744612- 1–744612-10, SPIE Proc. 7446, D. Van De Ville, V. K. Goyal, and M. Papadakis, eds., SPIE, Bellingham, WA, 2009. [link]
  • G. Kutyniok, M. Shahram, and D. L. Donoho. Development of a Digital Shearlet Transform Based on Pseudo-Polar FFT. Wavelets XIII (San Diego, CA, 2009), 74460B-1– 74460B-13 SPIE Proc. 7446, D. Van De Ville, V. K. Goyal, and M. Papadakis, eds., SPIE, Bellingham, WA, 2009. [link]
  • B. G. Bodmann, P. G. Casazza, G. Kutyniok, and S. Senger. A Low Complexity Replacement Scheme for Erased Frame. Wavelets XIII (San Diego, CA, 2009), 74460O-1– 74460O-10, SPIE Proc. 7446, D. Van De Ville, V. K. Goyal, and M. Papadakis, eds., SPIE, Bellingham, WA, 2009. [link]
  • B. G. Bodmann and G. Kutyniok. Erasure-Proof Transmissions: Fusion Frames meet Coding Theory. Wavelets XIII (San Diego, CA, 2009), 74460P-1–74460P-11, SPIE Proc. 7446, D. Van De Ville, V. K. Goyal, and M. Papadakis, eds., SPIE, Bellingham, WA, 2009. [link]
  • P. Boufounos, G. Kutyniok, and H. Rauhut. Compressed Sensing for Fusion Frames. Wavelets XIII (San Diego, CA, 2009), 744614-1–744614-11, SPIE Proc. 7446, D. Van De Ville, V. K. Goyal, and M. Papadakis, eds., SPIE, Bellingham, WA, 2009. [link]

2008

  • C. Heil and G. Kutyniok. Convolution and Wiener amalgam spaces on the affine group. In Recent Advances in Computational Science (Beijing, China, 2005), P. E. T. Jorgensen, X. Shen, C.-W. Shu, and N. Yan, eds., World Scientific, Singapore (2008), 209–217. [link]
  • P. G. Casazza and G. Kutyniok. Robustness of Fusion Frames under Erasures of Subspaces and of Local Frame Vectors. In Radon transforms, geometry, and wavelets (New Orleans, LA, 2006), E. L. Grinberg, D. Larson, P.E.T. Jorgensen, P. Massopust, G. Olafsson, E.T. Quinto, and B. Rubi, eds., Contemp. Math. 464, Amer. Math. Soc., Providence, RI, 2008, 149–160. [link]
  • A. Pezeshki, G. Kutyniok, and A. R. Calderbank. Fusion frames and Robust Dimension Reduction. 42nd Annual Conference on Information Sciences and Systems (CISS) (Princeton University, NJ, 2008), 2008, 264–268. [link]
  • D. L. Donoho and G. Kutyniok. Analysis of ' 1 Minimization in the Geometric Separation Problem. 42nd Annual Conference on Information Sciences and Systems (CISS) (Princeton University, NJ, 2008), 2008, 274–279. [link]

 2007 

  • P. G. Casazza, G. Kutyniok, S. Li, and C. J. Rozell. Modeling Sensor Networks with Fusion Frames. In Wavelets XII (San Diego, CA, 2007), 67011M-1–67011M-11, SPIE Proc. 6701, D. Van De Ville, V. K. Goyal, and M. Papadakis, eds., SPIE, Bellingham, WA (2007). [link]

2006

  •  K. Guo, G. Kutyniok, and D. Labate. Sparse Multidimensional Representations using Anisotropic Dilation and Shear Operators. In Wavelets and Splines (Athens, GA, 2005), G. Chen and M. J. Lai, eds., Nashboro Press, Nashville, TN (2006), 189–201. [link]

 2005

  • D. Labate, W-Q. Lim, G. Kutyniok, and G. Weiss. Sparse multidimensional representation using shearlets. In Wavelets XI (San Diego, CA, 2005), SPIE Proc. 5914, M. Papadakis, A. F. Laine, and M. A. Unser, eds., SPIE, Bellingham, WA (2005), 254–262. [link]
  • G. Ascensi and G. Kutyniok. Accumulative density. In Wavelets XI (San Diego, CA, 2005), SPIE Proc. 5914, M. Papadakis, A. F. Laine, and M. A. Unser, eds., SPIE, Bellingham, WA (2005), 188–195. [link]
  • P.G. Casazza, G. Kutyniok, and M.C. Lammers. Duality principles, localization of frames, and Gabor theory. In Wavelets XI (San Diego, CA, 2005), SPIE Proc. 5914, M. Papadakis, A. F. Laine, and M. A. Unser, eds., SPIE, Bellingham, WA (2005), 389–398. [link]
  • R. Balan, P.G. Casazza, D. Edidin, and G. Kutyniok. Decompositions of frames and a new frame identity. In Wavelets XI (San Diego, CA, 2005), SPIE Proc. 5914, M. Papadakis, A. F. Laine, and M. A. Unser, eds., SPIE, Bellingham, WA (2005), 379–388. [link]

2004 

  •  P.G. Casazza and G. Kutyniok. Frames of subspaces. In Wavelets, Frames and Operator Theory (College Park, MD, 2003), C. Heil, P. E. T. Jorgensen, and D. R. Larson, eds., Contemp. Math. 345, Amer. Math. Soc., Providence, RI (2004), 87–113. [link]

 2003

  • G. Kutyniok. Computation of the density of weighted wavelet systems. In Wavelets X (San Diego, CA, 2003), SPIE Proc. 5207, M. A. Unser, A. Aldroubi, and A. F. Laine, eds., SPIE, Bellingham, WA (2003), 393–404. [link]

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