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Shaowen Wang

4 papers hereh-index 11 citations8 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author2

Across the 4 of 4 papers where every author was matched, so the position is known.

fields
  • physics.geo-ph2
  • cs.LG1
  • physics.gen-ph1
same name
  • Shaowen Wang — 12 papers, h 5
  • Shaowen Wang — 6 papers, h 3
  • Shaowen Wang — 3 papers, h 2
  • Shaowen Wang — 1 paper, h 1
  • Shaowen Wang — 1 paper, h 1
  • Shaowen Wang — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

4 papers

physics.gen-ph2026

SWEEP (Seismic Wave Equation Exploration Platform): A Unified Solver Framework for Differentiable Wave Physics

Shaowen Wang, Tariq Alkhalifah

SWEEP (Seismic Wave Equation Exploration Platform) is a unified and extensible wave equation solver library designed for wavefield modeling and inversion. It supports a wide range…

cs.LG2026

Target noise: A pre-training based neural network initialization for efficient high resolution learning

Shaowen Wang, Tariq Alkhalifah

Weight initialization plays a crucial role in the optimization behavior and convergence efficiency of neural networks. Most existing initialization methods, such as Xavier and Kaim…

physics.geo-ph2025

High-resolution velocity model estimation with neural operator and the time-shift imaging condition

Xiao Ma, Shaowen Wang, Tariq Alkhalifah

Extracting subsurface velocity information from seismic data is mainly an undetermined problem that requires injecting a priori information to constrain the inversion process. Mach…

physics.geo-ph2025

Inspired by machine learning optimization: can gradient-based optimizers solve cycle skipping in full waveform inversion given sufficient iterations?

Xinru Mu, Omar M. Saad, Shaowen Wang +1

Full waveform inversion (FWI) iteratively updates the velocity model by minimizing the difference between observed and simulated data. Due to the high computational cost and memory…

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