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Eran Treister
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PDE-GCN: Novel architectures for graph neural networks motivated by partial differential equations
M Eliasof, E Haber, E Treister
Advances in neural information processing systems 34, 3836-3849, 2021
1582021
A fast marching algorithm for the factored eikonal equation
E Treister, E Haber
Journal of Computational Physics 324, 210-225, 2016
782016
IMEXnet: A forward stable deep neural network
E Haber, K Lensink, E Treister, L Ruthotto
International Conference on Machine Learning (ICML) 2019, 2525-2534, 2019
532019
A block-coordinate descent approach for large-scale sparse inverse covariance estimation
E Treister, JS Turek
Advances in neural information processing systems 27, 2014
482014
jInv--a flexible Julia package for PDE parameter estimation
L Ruthotto, E Treister, E Haber
SIAM Journal on Scientific Computing 39 (5), S702–S722, 2017
442017
Multigrid-augmented deep learning preconditioners for the Helmholtz equation
Y Azulay, E Treister
SIAM Journal on Scientific Computing 45 (3), S127-S151, 2022
372022
Non-Galerkin multigrid based on sparsified smoothed aggregation.
E Treister, I Yavneh
SIAM Journal on Scientific Computing (SISC) 37 (1), A30–A54, 2015
332015
Square and stretch multigrid for stochastic matrix eigenproblems
E Treister, I Yavneh
Numerical Linear Algebra with Applications 17 (2‐3), 229-251, 2010
312010
pathgcn: Learning general graph spatial operators from paths
M Eliasof, E Haber, E Treister
International conference on machine learning, 5878-5891, 2022
302022
DiffGCN: Graph Convolutional Networks via Differential Operators and Algebraic Multigrid Pooling
M Eliasof, E Treister
Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS) 2020, 2020
282020
Fast multilevel methods for Markov chains
HD Sterck, K Miller, E Treister, I Yavneh
Numerical Linear Algebra with Applications 18 (6), 961-980, 2011
282011
Full waveform inversion guided by travel time tomography
E Treister, E Haber
SIAM Journal on Scientific Computing 39 (5), S587–S609, 2017
272017
A multilevel iterated-shrinkage approach to l-1 penalized least-squares minimization
E Treister, I Yavneh
Signal Processing, IEEE Transactions on 60 (12), 6319-6329, 2012
272012
Improving Graph Neural Networks with Learnable Propagation Operators
M Eliasof, L Ruthotto, E Treister
40th International Conference on Machine Learning (ICML), 2022
252022
Feature Transportation Improves Graph Neural Networks
M Eliasof, E Haber, E Treister
AAAI Association for the Advancement of Artificial Intelligence, 2024
23*2024
On-the-fly adaptive smoothed aggregation multigrid for Markov chains
E Treister, I Yavneh
SIAM Journal on Scientific Computing 33 (5), 2927-2949, 2011
232011
Wavelet convolutions for large receptive fields
SE Finder, R Amoyal, E Treister, O Freifeld
European Conference on Computer Vision, 363-380, 2024
222024
NeRN--Learning Neural Representations for Neural Networks
M Ashkenazi, Z Rimon, R Vainshtein, S Levi, E Richardson, P Mintz, ...
The International Conference on Learning Representations (ICLR) 2023, 2023
202023
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks
J Ephrath, M Eliasof, L Ruthotto, E Haber, E Treister
IEEE Journal of Selected Topics in Signal Processing 14 (4), 894 - 904, 2020
162020
Wavelet Feature Maps Compression for Image-to-Image CNNs
SE Finder, Y Zohav, M Ashkenazi, E Treister
Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS …, 2022
132022
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