Michael Perlmutter
Michael Perlmutter
Department of Mathematics, University of California, Mathematics
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Magnet: A neural network for directed graphs
X Zhang, Y He, N Brugnone, M Perlmutter, M Hirn
Advances in Neural Information Processing Systems 34, 27003-27015, 2021
Understanding graph neural networks with asymmetric geometric scattering transforms
M Perlmutter, F Gao, G Wolf, M Hirn
arXiv preprint arXiv:1911.06253, 2019
Inverting spectrogram measurements via aliased Wigner distribution deconvolution and angular synchronization
M Perlmutter, S Merhi, A Viswanathan, M Iwen
Information and Inference: A Journal of the IMA 10 (4), 1491-1531, 2021
Lower Lipschitz bounds for phase retrieval from locally supported measurements
MA Iwen, S Merhi, M Perlmutter
Applied and Computational Harmonic Analysis 47 (2), 526-538, 2019
Geometric scattering on manifolds
M Perlmutter, G Wolf, M Hirn
arXiv preprint arXiv:1812.06968, 2018
Geometric wavelet scattering networks on compact Riemannian manifolds
M Perlmutter, F Gao, G Wolf, M Hirn
Mathematical and Scientific Machine Learning, 570-604, 2020
On a class of Calderón-Zygmund operators arising from projections of martingale transforms
M Perlmutter
Potential Analysis 42 (2), 383-401, 2015
Molecular Graph Generation via Geometric Scattering
D Bhaskar, JD Grady, MA Perlmutter, S Krishnaswamy
arXiv preprint arXiv:2110.06241, 2021
A new approach to large deviations for the Ginzburg-Landau model
S Banerjee, A Budhiraja, M Perlmutter
Electronic Journal of Probability 25, 1-51, 2020
Scattering statistics of generalized spatial poisson point processes
M Perlmutter, J He, M Hirn
ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022
Overcoming Oversmoothness in Graph Convolutional Networks via Hybrid Scattering Networks
F Wenkel, Y Min, M Hirn, M Perlmutter, G Wolf
arXiv preprint arXiv:2201.08932, 2022
The Manifold Scattering Transform for High-Dimensional Point Cloud Data
J Chew, HR Steach, S Viswanath, HT Wu, M Hirn, D Needell, ...
arXiv preprint arXiv:2206.10078, 2022
Taxonomy of Benchmarks in Graph Representation Learning
R Liu, S Cantürk, F Wenkel, D Sandfelder, D Kreuzer, A Little, S McGuire, ...
arXiv preprint arXiv:2206.07729, 2022
Can Hybrid Geometric Scattering Networks Help Solve the Maximal Clique Problem?
Y Min, F Wenkel, M Perlmutter, G Wolf
arXiv preprint arXiv:2206.01506, 2022
Modewise operators for low-rank tensor recovery
M Iwen, D Needell, M Perlmutter, E Rebrova
2022 Virtual Joint Mathematics Meetings (JMM 2022), 2022
On audio enhancement via online non-negative matrix factorization
A Sack, W Jiang, M Perlmutter, P Salanevich, D Needell
2022 56th Annual Conference on Information Sciences and Systems (CISS), 287-291, 2022
Toward Fast and Provably Accurate Near-field Ptychographic Phase Retrieval
M Iwen, M Perlmutter, MP Roach
arXiv preprint arXiv:2112.10804, 2021
Towards a Taxonomy of Graph Learning Datasets
R Liu, S Cantürk, F Wenkel, D Sandfelder, D Kreuzer, A Little, S McGuire, ...
arXiv preprint arXiv:2110.14809, 2021
Modewise Operators, the Tensor Restricted Isometry Property, and Low-Rank Tensor Recovery
MA Iwen, D Needell, M Perlmutter, E Rebrova
arXiv preprint arXiv:2109.10454, 2021
Phase Retrieval for via the Provably Accurate and Noise Robust Numerical Inversion of Spectrogram Measurements
M Iwen, M Perlmutter, N Sissouno, A Viswanathan
arXiv preprint arXiv:2106.02517, 2021
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