5 papers
Enforcing Reciprocity in Operator Learning for Seismic Wave Propagation
Caifeng Zou, Yaozhong Shi, Zachary E. Ross +2
Accurate and efficient wavefield modeling underpins seismic structure and source studies. Traditional methods comply with physical laws but are computationally intensive. Data-driv…
Large-Scale 3D Ground-Motion Synthesis with Physics-Inspired Latent Operator Flow Matching
Yaozhong Shi, Grigorios Lavrentiadis, Konstantinos Tsalouchidis +5
Earthquake hazard analysis and design of spatially distributed infrastructure, such as power grids and energy pipeline networks, require scenario-specific ground-motion time histor…
Ambient Noise Full Waveform Inversion with Neural Operators
Caifeng Zou, Zachary E. Ross, Robert W. Clayton +2
Numerical simulations of seismic wave propagation are crucial for investigating velocity structures and improving seismic hazard assessment. However, standard methods such as finit…
InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences
Hongkai Zheng, Wenda Chu, Bingliang Zhang +9
Plug-and-play diffusion priors (PnPDP) have emerged as a promising research direction for solving inverse problems. However, current studies primarily focus on natural image restor…
Reducing Frequency Bias of Fourier Neural Operators in 3D Seismic Wavefield Simulations Through Multi-Stage Training
Qingkai Kong, Caifeng Zou, Youngsoo Choi +5
The recent development of Neural Operator (NeurOp) learning for solutions to the elastic wave equation shows promising results and provides the basis for fast large-scale simulatio…