15 citations · 23 across the 12 of their papers we have counts for
13 papers
Distributed Proximal Stein Variational Gradient Descent Algorithm for Large-scale Bayesian Inference in Traveltime Tomography
Akshay Vishwakarma, Kamal Aghazade, Ali Siahkoohi +1
We present a distributed framework for large-scale Bayesian inverse problems governed by the eikonal equation, with a specific focus on seismic traveltime tomography. Traditional d…
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…
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…
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…
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…
Robust elastic full-waveform inversion using an alternating direction method of multipliers with reconstructed wavefields
Kamal Aghazade, Ali Gholami, Hossein S. Aghamiry +1
Elastic full-waveform inversion (EFWI) is a process used to estimate subsurface properties by fitting seismic data while satisfying wave propagation physics. The problem is formula…
Full Waveform Inversion and Lagrange Multipliers
Ali Gholami
Full-waveform inversion (FWI) is an effective method for imaging subsurface properties using sparsely recorded data. It involves solving a wave propagation problem to estimate mode…
Large-scale highly-accurate extended full waveform inversion using convergent Born series
Hossein S. Aghamiry, Ali Gholami, Kamal Aghazade +2
Full-waveform inversion (FWI) is a seismic imaging method that provides quantitative inference about subsurface properties with a wavelength-scale resolution. Its frequency-domain…
Randomized source sketching for full waveform inversion
Kamal Aghazade, Hossein S. Aghamiry, Ali Gholami +1
Partial differential equation (PDE) constrained optimization problems such as seismic full waveform inversion (FWI) frequently arise in the geoscience and related fields. For such…
Anderson accelerated augmented Lagrangian for extended waveform inversion
Kamal Aghazade, Ali Gholami, Hossein S Aghamiry +1
The augmented Lagrangian (AL) method provides a flexible and efficient framework for solving extended-space full-waveform inversion (FWI), a constrained nonlinear optimization prob…
Robust and high-resolution seismic complex trace analysis
M. Kazemnia Kakhki, W. J. Mansur, K. Aghazadeh
Seismic attributes calculated by conventional methods are susceptible to noise. Conventional filtering reduces the noise in the cost of losing the spectral bandwidth. The challenge…