5 papers
Full waveform inversion method based on diffusion model
Caiyun Liu, Siyang Pei, Qingfeng Yu +1
Seismic full-waveform inversion is a core technology for obtaining high-resolution subsurface model parameters. However, its highly nonlinear characteristics and strong dependence…
High-Fidelity Compression of Seismic Velocity Models via SIREN Auto-Decoders
Caiyun Liu, Xiaoxue Luo, Jie Xiong
Implicit Neural Representations (INRs) have emerged as a powerful paradigm for representing continuous signals independently of grid resolution. In this paper, we propose a high-fi…
Conditional Rectified Flow-based End-to-End Rapid Seismic Inversion Method
Haofei Xu, Wei Cheng, Sizhe Li +1
Seismic inversion is a core problem in geophysical exploration, where traditional methods suffer from high computational costs and are susceptible to initial model dependence. In r…
Seismic full-waveform inversion based on a physics-driven generative adversarial network
Xinyi Zhang, Caiyun Liu, Jie Xiong +1
Objectives: Full-waveform inversion (FWI) is a high-resolution geophysical imaging technique that reconstructs subsurface velocity models by iteratively minimizing the misfit betwe…
AIMatDesign: Knowledge-Augmented Reinforcement Learning for Inverse Materials Design under Data Scarcity
Yeyong Yu, Xilei Bian, Jie Xiong +2
With the growing demand for novel materials, machine learning-driven inverse design methods face significant challenges in reconciling the high-dimensional materials composition sp…