6 papers
Scalable Bayesian full waveform inversion via dual augmented Lagrangian SVGD
Kamal Aghazade, Ali Siahkoohi, Ali Gholami
Full waveform inversion is an ill-posed inverse problem whose solution non-uniqueness -- i.e., arising from band-limited, finite-aperture, noisy data -- calls for uncertainty quant…
Dual-space posterior sampling for Bayesian inference in constrained inverse problems
Ali Siahkoohi, Kamal Aghazade, Ali Gholami
Inverse problems constrained by partial differential equations are often ill-conditioned due to noisy, incomplete data or inherent non-uniqueness. A prominent example is full wavef…
Automatic Penalty Parameter Selection by Residual Whiteness Principle (RWP) and GCV for Full Waveform Inversion
Kamal Aghazade, Toktam Zand, Ali Gholami
Full-waveform inversion (FWI) is a powerful seismic imaging technique used to estimate high-resolution physical properties of subsurface structures by minimizing the misfit between…
Robust acoustic and elastic full waveform inversion by adaptive Tikhonov-TV regularization
Kamal Aghazade, Ali Gholami
Full Waveform Inversion (FWI) is a powerful wave-based imaging technique, but its inherent ill-posedness and non-convexity lead to local minima and poor convergence. Regularization…
Weighted Lagrange Multiplier Method for Robust Source-Independent Waveform Inversion
Ali Gholami, Kamal Aghazade, Akshay Vishwakarma
The Lagrange multiplier method has proven highly effective for mitigating the ill-conditioning of full waveform inversion (FWI), enabling robust and computationally efficient algor…
Fast and Automatic Full Waveform Inversion by Dual Augmented Lagrangian
Kamal Aghazade, Ali Gholami
Full Waveform Inversion (FWI) stands as a nonlinear, high-resolution technology for subsurface imaging via surface-recorded data. This paper introduces an augmented Lagrangian dual…