Thomas Wiatowski
Dr. sc. ETH Zurich, M.Sc. in Mathematics |
Additional Information
You can find me on LinkedIn and ResearchGate.
Invited speaker at the Mathematics of Deep Learning workshop in Berlin, Germany, September 2017.
Co-organizer of the minisymposium Deep Neural Networks: Theory and Application at the Applied Inverse Problems (AIP) conference in Hangzhou, China, May 2017.
Note: Thomas Wiatowski is no longer with our group.
Publications
- Journal Papers and Manuscripts
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Energy propagation in deep convolutional neural networks
T. Wiatowski, P. Grohs, and H. Bölcskei, IEEE Transactions on Information Theory, Vol. 64, No. 7, pp. 4819-4842, July 2018. -
A mathematical theory of deep convolutional neural networks for feature extraction
T. Wiatowski and H. Bölcskei, IEEE Transactions on Information Theory, Vol. 64, No. 3, pp. 1845-1866, Mar. 2018.
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Energy propagation in deep convolutional neural networks
- Conference, Symposium, and Workshop Papers
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Deep structured features for semantic segmentation
M. Tschannen, L. Cavigelli, F. Mentzer, T. Wiatowski, and L. Benini, Proc. of European Signal Processing Conference (EUSIPCO), pp. 61-65, Sept. 2017. -
Topology reduction in deep convolutional feature extraction networks
T. Wiatowski, P. Grohs, and H. Bölcskei, Proc. of SPIE (Wavelets and Sparsity XVII), San Diego, CA, USA, Vol. 10394, pp. 1039418:1-1039418:12, Aug. 2017, (invited paper). -
Energy decay and conservation in deep convolutional neural networks
P. Grohs, T. Wiatowski, and H. Bölcskei, Proc. of IEEE International Symposium on Information Theory (ISIT), Aachen, Germany, pp. 1356-1360, June 2017. -
Heart sound classification using deep structured features
M. Tschannen, T. Kramer, G. Marti, M. Heinzmann, and T. Wiatowski, Computing in Cardiology (CinC), Vancouver, Canada, pp. 565-568, Sept. 2016. -
Deep convolutional neural networks on cartoon functions
P. Grohs, T. Wiatowski, and H. Bölcskei, Proc. of IEEE International Symposium on Information Theory (ISIT), Barcelona, Spain, pp. 1163-1167, July 2016. -
Discrete deep feature extraction: A theory and new architectures
T. Wiatowski, M. Tschannen, A. Stanić, P. Grohs, and H. Bölcskei, Proc. of International Conference on Machine Learning (ICML), New York, USA, pp. 2149-2158, June 2016. -
Deep convolutional neural networks based on semi-discrete frames
T. Wiatowski and H. Bölcskei, Proc. of IEEE International Symposium on Information Theory (ISIT), Hong Kong, China, pp. 1212-1216, June 2015.
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Deep structured features for semantic segmentation
- Theses
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Harmonic analysis of deep convolutional neural networks
T. Wiatowski, Doctoral Thesis, ETH Zurich, Switzerland, Aug. 2017. -
Kernel based image reconstruction from spherical Radon data
T. Wiatowski, Master's Thesis, TU München, Germany, Nov. 2012. -
Evolution of angular momentum expectation in quantum mechanics
T. Wiatowski, Bachelor's Thesis, TU München, Germany, Aug. 2010.
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Harmonic analysis of deep convolutional neural networks
Supervised Theses
- Diploma Theses
- Noll, Andreas, "Topology Considerations in Scattering Networks," Fall semester 2017
Supervisor(s): Thomas Wiatowski - Thandiackal, Kevin, "Wavelet-Based Convolutional Neural Networks for Reinforcement Learning," Spring semester 2016
Supervisor(s): Michael Tschannen, Thomas Wiatowski - Stanić, Aleksandar, "Discrete Generalized Scattering Transform," Spring semester 2015
Supervisor(s): Thomas Wiatowski - Cavigelli, Lukas, "Invariant Scattering Convolution Networks," Fall semester 2013
Supervisor(s): Thomas Wiatowski, Céline Aubel
- Noll, Andreas, "Topology Considerations in Scattering Networks," Fall semester 2017
- Student Projects
- Giacomuzzi, Sandro, "Rate of Energy Decay in Deep Convolutional Neural Networks," Fall semester 2017
Supervisor(s): Thomas Wiatowski - Belkhayat, Kamil, "Statistical Arbitrage: Systematic Equity Pairs Trading," Spring semester 2017
Supervisor(s): Thomas Wiatowski - Mentzer, Fabian, "Scene Labeling Using Deep Structured Features," Spring semester 2016
Supervisor(s): Michael Tschannen, Lukas Cavigelli, Thomas Wiatowski, Michael Lerjen - Kühne, Jonas, "Scattering Networks for Scene Labeling," Fall semester 2015
Supervisor(s): Michael Tschannen, Lukas Cavigelli, Thomas Wiatowski, Michael Lerjen - Geiger, Christian, "Feature Importance of Scattering Coefficients in Facial Landmark Detection," Fall semester 2015
Supervisor(s): Michael Tschannen, Thomas Wiatowski - Thandiackal, Kevin, "Scattering Networks with Haar Wavelets," Spring semester 2015
Supervisor(s): Thomas Wiatowski - Marti, Fabio, "Meshfree Approximation of High-Dimensional Data," Fall semester 2013
Supervisor(s): Thomas Wiatowski
- Giacomuzzi, Sandro, "Rate of Energy Decay in Deep Convolutional Neural Networks," Fall semester 2017
- Group Projects
- Heinzmann, Matthias; Kramer, Thomas; Marti, Gian, "A Python Implementation for Deep Structured Feature Extraction," Spring semester 2016
Supervisor(s): Thomas Wiatowski, Michael Tschannen
- Heinzmann, Matthias; Kramer, Thomas; Marti, Gian, "A Python Implementation for Deep Structured Feature Extraction," Spring semester 2016
Talks
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Harmonic analysis of deep convolutional neural networks
T. Wiatowski, Google Brain, Zurich, Switzerland, Nov. 2017, (invited talk). -
Deep convolutional neural networks from a harmonic analysis perspective
T. Wiatowski, Mathematics of Deep Learning, Workshop organized by the Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany, Sept. 2017, (invited talk). -
Topology reduction in deep convolutional feature extraction networks
T. Wiatowski, Wavelets and Sparsity XVII, San Diego, USA, Aug. 2017, (invited talk). -
Harmonic analysis of deep convolutional neural networks
T. Wiatowski, Applied Inverse Problems Conference, Hangzhou, China, May 2017, (invited talk). -
A mathematical theory of deep convolutional neural networks for feature extraction
T. Wiatowski, Deep Learning: Theory and Practice, Workshop organized by the Max Planck Institute for Intelligent Systems, Donaueschingen, Germany, July 2016, (invited talk). -
Generic properties of scattering networks
T. Wiatowski, Institute of Theoretical Information Technology, TU München, Germany, June 2016, (invited talk). -
Fast algebraic reconstruction for photoacoustic tomography
T. Wiatowski, Institute of Computational Biology, Helmholtz Zentrum, Munich, Germany, Dec. 2013, (invited talk). -
Fast kernel-based reconstruction from spherical mean data
T. Wiatowski, Applied Inverse Problems Conference, Daejeon, South Korea, July 2013, (invited talk).