activity
20172023
most citedUnsupervised Learning of Full-Waveform Inversion: Connecting CNN and Partial Differential Equation in a Loop

24 citations · 56 across the 9 of their papers we have counts for

collaborators

9 papers

cs.LG2023

An Empirical Study of Large-Scale Data-Driven Full Waveform Inversion

Peng Jin, Yinan Feng, Shihang Feng +5

This paper investigates the impact of big data on deep learning models to help solve the full waveform inversion (FWI) problem. While it is well known that big data can boost the p…

physics.geo-ph2023★ 4 cited

: Multi-parameter Benchmark Datasets for Elastic Full Waveform Inversion of Geophysical Properties

Shihang Feng, Hanchen Wang, Chengyuan Deng +6

Elastic geophysical properties (such as P- and S-wave velocities) are of great importance to various subsurface applications like CO sequestration and energy exploration (e.g.,…

physics.geo-ph2023★ 4 cited

Auto-Linear Phenomenon in Subsurface Imaging

Yinan Feng, Yinpeng Chen, Peng Jin +3

Subsurface imaging involves solving full waveform inversion (FWI) to predict geophysical properties from measurements. This problem can be reframed as an image-to-image translation…

cs.LG2022★ 4 cited

An Intriguing Property of Geophysics Inversion

Yinan Feng, Yinpeng Chen, Shihang Feng +3

Inversion techniques are widely used to reconstruct subsurface physical properties (e.g., velocity, conductivity) from surface-based geophysical measurements (e.g., seismic, electr…

physics.geo-ph2022★ 2 cited

Extremely Weak Supervision Inversion of Multi-physical Properties

Shihang Feng, Peng Jin, Xitong Zhang +4

Multi-physical inversion plays a critical role in geophysics. It has been widely used to infer various physical properties~(such as velocity and conductivity). Among those inversio…

cs.LG2021★ 14 cited

OpenFWI: Large-Scale Multi-Structural Benchmark Datasets for Seismic Full Waveform Inversion

Chengyuan Deng, Shihang Feng, Hanchen Wang +6

Full waveform inversion (FWI) is widely used in geophysics to reconstruct high-resolution velocity maps from seismic data. The recent success of data-driven FWI methods results in…

cs.LG2021★ 24 cited

Unsupervised Learning of Full-Waveform Inversion: Connecting CNN and Partial Differential Equation in a Loop

Peng Jin, Xitong Zhang, Yinpeng Chen +3

This paper investigates unsupervised learning of Full-Waveform Inversion (FWI), which has been widely used in geophysics to estimate subsurface velocity maps from seismic data. Thi…

cs.LG2019★ 2 cited

Adversarial Sub-sequence for Text Generation

Xingyuan Chen, Yanzhe Li, Peng Jin +4

Generative adversarial nets (GAN) has been successfully introduced for generating text to alleviate the exposure bias. However, discriminators in these models only evaluate the ent…

cs.LG2017★ 2 cited

Restricted Boltzmann Machines with Gaussian Visible Units Guided by Pairwise Constraints

Jielei Chu, Hongjun Wang, Hua Meng +2

Restricted Boltzmann machines (RBMs) and their variants are usually trained by contrastive divergence (CD) learning, but the training procedure is an unsupervised learning approach…