13 citations · 22 across the 4 of their papers we have counts for
8 papers
Wave simulation in non-smooth media by PINN with quadratic neural network and PML condition
Yanqi Wu, Hossein S. Aghamiry, Stephane Operto +1
Frequency-domain simulation of seismic waves plays an important role in seismic inversion, but it remains challenging in large models. The recently proposed physics-informed neural…
Revisit Geophysical Imaging in A New View of Physics-informed Generative Adversarial Learning
Fangshu Yang, Jianwei Ma
Seismic full waveform inversion (FWI) is a powerful geophysical imaging technique that produces high-resolution subsurface models by iteratively minimizing the misfit between the s…
Data-driven geophysics: from dictionary learning to deep learning
Siwei Yu, Jianwei Ma
Understanding the principles of geophysical phenomena is an essential and challenging task. "Model-driven" approaches have supported the development of geophysics for a long time;…
Deep-learning inversion: a next generation seismic velocity-model building method
Fangshu Yang, Jianwei Ma
Seismic velocity is one of the most important parameters used in seismic exploration. Accurate velocity models are key prerequisites for reverse-time migration and other high-resol…
Can learning from natural image denoising be used for seismic data interpolation?
Hao Zhang, Xiuyan Yang, Jianwei Ma
We propose a convolutional neural network (CNN) denoising based method for seismic data interpolation. It provides a simple and efficient way to break though the lack problem of ge…
Enhanced image approximation using shifted rank-1 reconstruction
Florian Boßmann, Jianwei Ma
Low rank approximation has been extensively studied in the past. It is most suitable to reproduce rectangular like structures in the data. In this work we introduce a generalizatio…