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Thomas Dittrich
Thomas Dittrich
Radon Institute for Computational and Applied Mathematics
Verified email at ricam.oeaw.ac.at
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Cited by
Year
Flexible multi-node simulation of cellular mobile communications: the Vienna 5G System Level Simulator
MK Müller, F Ademaj, T Dittrich, A Fastenbauer, B Ramos Elbal, A Nabavi, ...
EURASIP Journal on Wireless Communications and Networking 2018, 1-17, 2018
1422018
Signal Processing on Signed Graphs: Fundamentals and Potentials
T Dittrich, G Matz
IEEE Signal Processing Magazine 37 (6), 86-98, 2020
182020
Semi-supervised Multiclass Clustering Based on Signed Total Variation
P Berger, T Dittrich, G Hannak, G Matz
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and …, 2019
102019
Semi-Supervised Clustering Based on Signed Total Variation
P Berger, T Dittrich, G Matz
2018 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2018
92018
Learning Signed Graphs from Data
G Matz, T Dittrich
ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020
82020
Semi-Supervised Spectral Clustering Using the Signed Laplacian
T Dittrich, P Berger, G Matz
2018 52nd Asilomar Conference on Signals, Systems, and Computers, 1413-1417, 2018
72018
An Efficient Method for Avoiding Shadow Fading Maps in System Level Simulations
T Dittrich, M Taranetz, M Rupp
WSA 2017; 21th International ITG Workshop on Smart Antennas, 1-8, 2017
62017
Signature Graphs—Fundamentals, Learning, and Clustering
G Matz, T Dittrich
2022 56th Asilomar Conference on Signals, Systems, and Computers, 235-239, 2022
22022
Unsupervised Clustering on Signed Graphs with Unknown Number of Clusters
T Dittrich, G Matz
2020 28th European Signal Processing Conference (EUSIPCO), 1060-1064, 2021
22021
Non-Convex Total Variation Minimization for Signed Graph Cut Clustering
T Dittrich, G Matz
2021 55th Asilomar Conference on Signals, Systems, and Computers, 1307-1311, 2021
22021
Space-Time Approximation with Shallow Neural Networks in Fourier Lebesgue spaces
A Abdeljawad, T Dittrich
arXiv preprint arXiv:2312.08461, 2023
12023
A Linearly Constrained Power Iteration for Spectral Semi-Supervised Classification on Signed Graphs
T Dittrich, G Matz
2022 IEEE Data Science and Learning Workshop (DSLW), 1-6, 2022
12022
A Maximum A Posteriori Relaxation For Clustering The Labeled Stochastic Block Model
T Dittrich, G Matz
2021 29th European Signal Processing Conference (EUSIPCO), 2194-2198, 2021
12021
The Vienna 5G System Level Simulator
M Müller, F Ademaj, A Fastenbauer, A Nabavi, T Dittrich, BR Elbal, ...
12020
Clustering on Dynamic Graphs Based on Total Variation
P Berger, T Dittrich, G Matz
2019 13th International conference on Sampling Theory and Applications …, 2019
12019
Efficient Learning of Balanced Signature Graphs
G Matz, C Verardo, T Dittrich
ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023
2023
Variational Methods for Semi-Supervised Node Classification on Signed Graphs with Multiple Classes
T Dittrich
Technische Universität Wien, 2023
2023
Spectral clustering with sampling; a graph signal processing perspective
T Dittrich
Wien, 2018
2018
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