Eldad Haber
Eldad Haber
Professor of Mathematics and Geophysics UBC
Verified email at eoas.ubc.ca
Cited by
Cited by
On optimization techniques for solving nonlinear inverse problems
E Haber, UM Ascher, D Oldenburg
Inverse problems 16 (5), 1263, 2000
Joint inversion: a structural approach
E Haber, D Oldenburg
Inverse problems 13 (1), 63, 1997
Intensity gradient based registration and fusion of multi-modal images
E Haber, J Modersitzki
International Conference on Medical Image Computing and Computer-Assisted …, 2006
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
RESINVM3D: A 3D resistivity inversion package
A Pidlisecky, E Haber, R Knight
Geophysics 72 (2), H1-H10, 2007
Stable architectures for deep neural networks
E Haber, L Ruthotto
Inverse Problems 34 (1), 014004, 2017
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
Numerical methods for volume preserving image registration
E Haber, J Modersitzki
Inverse problems 20 (5), 1621, 2004
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
Preconditioned all-at-once methods for large, sparse parameter estimation problems
E Haber, UM Ascher
Inverse Problems 17 (6), 1847, 2001
Three dimensional inversion of multisource time domain electromagnetic data
DW Oldenburg, E Haber, R Shekhtman
Geophysics 78 (1), E47-E57, 2013
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
Intensity gradient based registration and fusion of multi-modal images
E Haber, J Modersitzki
Methods of information in medicine 46 (03), 292-299, 2007
A multilevel method for image registration
E Haber, J Modersitzki
SIAM Journal on Scientific Computing 27 (5), 1594-1607, 2006
A GCV based method for nonlinear ill-posed problems
E Haber, D Oldenburg
Computational Geosciences 4 (1), 41-63, 2000
Deep neural networks motivated by partial differential equations
L Ruthotto, E Haber
Journal of Mathematical Imaging and Vision, 1-13, 2019
Numerical methods for coupled super-resolution
J Chung, E Haber, J Nagy
Inverse Problems 22 (4), 1261, 2006
Numerical methods for experimental design of large-scale linear ill-posed inverse problems
E Haber, L Horesh, L Tenorio
Inverse Problems 24 (5), 055012, 2008
Reversible architectures for arbitrarily deep residual neural networks
B Chang, L Meng, E Haber, L Ruthotto, D Begert, E Holtham
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
Inversion of time domain three-dimensional electromagnetic data
E Haber, DW Oldenburg, R Shekhtman
Geophysical Journal International 171 (2), 550-564, 2007
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