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Eldad Haber
Eldad Haber
Professor of Mathematics and Geophysics UBC
Verified email at eoas.ubc.ca
Title
Cited by
Cited by
Year
Stable architectures for deep neural networks
E Haber, L Ruthotto
Inverse problems 34 (1), 014004, 2017
7382017
Deep neural networks motivated by partial differential equations
L Ruthotto, E Haber
Journal of Mathematical Imaging and Vision 62 (3), 352-364, 2020
4832020
Joint inversion: a structural approach
E Haber, D Oldenburg
Inverse problems 13 (1), 63, 1997
4141997
On optimization techniques for solving nonlinear inverse problems
E Haber, UM Ascher, D Oldenburg
Inverse problems 16 (5), 1263, 2000
4042000
Reversible architectures for arbitrarily deep residual neural networks
B Chang, L Meng, E Haber, L Ruthotto, D Begert, E Holtham
Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018
2932018
Fast simulation of 3D electromagnetic problems using potentials
E Haber, UM Ascher, DA Aruliah, DW Oldenburg
Journal of Computational Physics 163 (1), 150-171, 2000
2902000
Intensity gradient based registration and fusion of multi-modal images
E Haber, J Modersitzki
Medical Image Computing and Computer-Assisted Intervention–MICCAI 2006: 9th …, 2006
2872006
Three dimensional inversion of multisource time domain electromagnetic data
DW Oldenburg, E Haber, R Shekhtman
Geophysics 78 (1), E47-E57, 2013
2742013
RESINVM3D: A 3D resistivity inversion package
A Pidlisecky, E Haber, R Knight
Geophysics 72 (2), H1-H10, 2007
2712007
Inversion of 3D electromagnetic data in frequency and time domain using an inexact all-at-once approach
E Haber, UM Ascher, DW Oldenburg
Geophysics 69 (5), 1216-1228, 2004
2342004
AntisymmetricRNN: A dynamical system view on recurrent neural networks
B Chang, M Chen, E Haber, EH Chi
arXiv preprint arXiv:1902.09689, 2019
2232019
Fast finite volume simulation of 3D electromagnetic problems with highly discontinuous coefficients
E Haber, UM Ascher
SIAM Journal on Scientific Computing 22 (6), 1943-1961, 2001
2222001
Numerical methods for volume preserving image registration
E Haber, J Modersitzki
Inverse problems 20 (5), 1621, 2004
2092004
Preconditioned all-at-once methods for large, sparse parameter estimation problems
E Haber, UM Ascher
Inverse Problems 17 (6), 1847, 2001
2082001
An introduction to deep generative modeling
L Ruthotto, E Haber
GAMM‐Mitteilungen 44 (2), e202100008, 2021
1982021
Multi-level residual networks from dynamical systems view
B Chang, L Meng, E Haber, F Tung, D Begert
arXiv preprint arXiv:1710.10348, 2017
1792017
An effective method for parameter estimation with PDE constraints with multiple right-hand sides
E Haber, M Chung, F Herrmann
SIAM Journal on Optimization 22 (3), 739-757, 2012
1772012
Computational methods in geophysical electromagnetics
E Haber
Society for Industrial and Applied Mathematics, 2014
1732014
A GCV based method for nonlinear ill-posed problems
E Haber, D Oldenburg
Computational Geosciences 4, 41-63, 2000
1732000
Intensity gradient based registration and fusion of multi-modal images
E Haber, J Modersitzki
Methods of information in medicine 46 (03), 292-299, 2007
1692007
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