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Related papers: Transdimensional 2D Full-Waveform Inversion and Un…

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Whole Slide Image (WSI) classification relies on Multiple Instance Learning (MIL) with spatial patch features, yet existing methods struggle to capture global dependencies due to the immense size of WSIs and the local nature of patch…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Anthony Bilic , Guangyu Sun , Ming Li , Md Sanzid Bin Hossain , Yu Tian , Wei Zhang , Laura Brattain , Dexter Hadley , Chen Chen

Recent developments in application of deep learning models to acoustic Full Waveform Inversion (FWI) are marked by the use of diffusion models as prior distributions for Bayesian-like inference procedures. The advantage of these methods is…

Machine Learning · Computer Science 2025-06-19 A. S. Stankevich , I. B. Petrov

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 methods stabilize FWI by incorporating prior information…

Geophysics · Physics 2025-10-28 Kamal Aghazade , Ali Gholami

Marine seismic exploration is a core technology supporting marine resource exploration, seabed detection, carbon sequestration monitoring, and offshore engineering safety. The integration of full-waveform inversion (FWI), elastic inversion,…

Geophysics · Physics 2026-05-05 Guoxin Chen

We present EUWA310, a seismic velocity model obtained by full seismic waveform inversion (FWI) model of the upper mantle beneath Europe and Western Asia. Inferred via 310 quasi-Newton updates from more than 260$\,$000 three-component…

In salt provinces, full-waveform inversion (FWI) is most likely to fail when starting with a poor initial model that lacks the salt information. Conventionally, salt bodies are included in the FWI starting model by interpreting the salt…

Geophysics · Physics 2023-04-07 Abdullah Alali , Tariq Alkhalifah

Efficient high-rank approximations of the Hessian can accelerate seismic full waveform inversion (FWI) and uncertainty quantification (UQ). In FWI, approximations of the inverse of the Hessian may be used as preconditioners for Newton-type…

Numerical Analysis · Mathematics 2025-08-12 Mathew Hu , Nick Alger , Rami Nammour , Omar Ghattas

Computational imaging plays a vital role in various scientific and medical applications, such as Full Waveform Inversion (FWI), Computed Tomography (CT), and Electromagnetic (EM) inversion. These methods address inverse problems by…

Machine Learning · Computer Science 2024-10-14 Yinan Feng , Yinpeng Chen , Yueh Lee , Youzuo Lin

We are concerned with high-fidelity subsurface imaging of the soil, which commonly arises in geotechnical site characterization and geophysical explorations. Specifically, we attempt to image the spatial distribution of the Lame parameters…

Numerical Analysis · Mathematics 2015-10-28 Arash Fathi , Loukas F. Kallivokas , Babak Poursartip

Due to its non-invasive and non-radiating nature, along with its low cost, ultrasound (US) imaging is widely used in medical applications. Typical B-mode US images have limited resolution and contrast and weak physical interpretation.…

Signal Processing · Electrical Eng. & Systems 2022-05-18 Avner Shultzman , Yonina C. Eldar

This paper is devoted to theoretical and numerical investigation of the local minimum issue in seismic full waveform inversion (FWI). This paper provides a mathematical analysis of optimal transportation (OT) type objective function's…

Numerical Analysis · Mathematics 2021-09-01 Lingyun Qiu

In the last ten years, full-waveform inversion has emerged as a robust and efficient high-resolution velocity model-building tool for seismic imaging, with the unique ability to recover complex subsurface structures. Originally based on a…

Geophysics · Physics 2021-06-17 Jérémie Messud , Raphaël Poncet , Gilles Lambaré

Partial differential equation (PDE) constrained optimization problems such as seismic full waveform inversion (FWI) frequently arise in the geoscience and related fields. For such problems, many observations are usually gathered by multiple…

Geophysics · Physics 2022-05-04 Kamal Aghazade , Hossein S. Aghamiry , Ali Gholami , Stephane Operto

Interferometric inversion involves recovery of a signal from cross-correlations of its linear transformations. A close relative of interferometric inversion is the generalized phase retrieval problem, which consists of recovering a signal…

Signal Processing · Electrical Eng. & Systems 2020-11-10 Bariscan Yonel , Birsen Yazici

Efficient frequency-domain Full Waveform Inversion (FWI) of long-offset node data can be designed with a few discrete frequencies hence allowing for compact volume of data to be managed. Moreover, attenuation effects can be…

Analysis of PDEs · Mathematics 2021-10-29 P. -H. Tournier , P. Jolivet , V. Dolean , H. S. Aghamiry , S. Operto , S. Riffo

This paper concerns the Time-Domain Full Waveform Inversion (FWI) for dispersive and dissipative poroelastic materials. The forward problem is an initial boundary value problem (IBVP) of the poroelastic equations with a memory term; the FWI…

Numerical Analysis · Mathematics 2022-01-24 Miao-jung Yvonne Ou , Petr Plecháč , Jiangming Xie

Micro-seismic events, naturally occurring within geological formations and quasi-brittle engineered systems, provide a powerful window into the evolving processes of material degradation and failure. Accurate characterization of these…

Geophysics · Physics 2024-01-18 A. A. M. da Silva , A. A. Novotnty , A. A. S. Amad , B. B. Guzina

Frequency-domain Full Waveform Inversion (FWI) is potentially amenable to efficient processing of full-azimuth long-offset stationary-recording seabed acquisition carried out with sparse layout of ocean bottom nodes (OBNs) and broadband…

Remotely sensed imagery interpretation (RSII) faces the three major problems: (1) objective representation of spatial distribution patterns; (2) edge uncertainty problem caused by downsampling encoder and intrinsic edge noises (e.g., mixed…

Computer Vision and Pattern Recognition · Computer Science 2025-05-30 Pengfei Zhang , Chang Li , Yongjun Zhang , Rongjun Qin , Kyle Gao , Jonathan Li

The Multilevel Monte Carlo method is an efficient variance reduction technique. It uses a sequence of coarse approximations to reduce the computational cost in uncertainty quantification applications. The method is nowadays often considered…

Numerical Analysis · Mathematics 2018-06-15 Pieterjan Robbe , Dirk Nuyens , Stefan Vandewalle
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