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M. Bronstein, and G. Kutyniok.|
Transferability of Spectral Graph Convolutional Neural Networks. 
|2||R. Levie and H. Avron|
Stochastic Phase space Signal Processing with Application to Localizing Phase Vocoder 
|3||R. Levie and N. Sochen|
A Wavelet Plancherel Theory with Application to Sparse Continuous Wavelet Transform 
F. Monti, X. Bresson, and M. Bronstein|
CayleyNets: Graph Convolutional Neural Networks with Complex Rational Spectral Filters 
IEEE Transactions on Signal Processing, vol 67, no. 1, 97-109, 2019.
|2||R. Levie and N. Sochen|
Uncertainty Principles and Optimally Sparse Wavelet Transforms 
Applied and Computational Harmonic Analysis, ISSN 1063-5203, 2018.
|3||R. Levie, H. G. Stark, F. Lieb
and N. Sochen|
Adjoint Translation, Adjoint Observable and Uncertainty Principle 
Advances in Computational Mathematics , vol 40,no. 3, 609-627, 2014.
Levie, C. Yapar, G. Kutyniok, and G. Caire|
Pathloss Prediction using Deep Learning with Applications to Cellular Optimization and Efficient D2D Link Scheduling
45th International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 (submitted)
|2||R. Levie, W.
Huang, L. Bucci, M. Bronstein, and G. Kutyniok|
Transferability of Spectral Graph Convolutional Neural Networks 
NeurIPS, Graph Representation Learning, 2019.
|3||R. Levie, E. Isufi and G.
On the Transferability of Spectral Graph Filters 
Proceedings of the 2019 IEEE International Conference on Sampling Theory and Applications (SAMPTA)}. 2019.
|4||D. Lantzberg, F. Lieb, H.-G.
Stark, R. Levie, and N. Sochen|
Uncertainty Principles, Minimum Uncertainty Samplings and Translations 
Proceedings of the 20th European Signal Processing Conference 2012 (EUSIPCO)
Representation Approach to Localization in Signal Processing|
PhD Thesis, Tel Aviv University, 2018
Advisor: Prof. Nir Sochen.
|2||Line Cross-Section Models:
Hybrid Volume-Surface Models of 3D Objects |
Master Thesis, Tel Aviv University, 2014
Advisors: Prof. Nira Dyn and Dr. Elza Farkhi.