April 26, 2024, 4:42 a.m. | Peng Jin, Yinan Feng, Shihang Feng, Hanchen Wang, Yinpeng Chen, Benjamin Consolvo, Zicheng Liu, Youzuo Lin

cs.LG updates on arXiv.org arxiv.org

arXiv:2307.15388v2 Announce Type: replace
Abstract: 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 performance of deep learning models in many tasks, its effectiveness has not been validated for FWI. To address this gap, we present an empirical study that investigates how deep learning models in FWI behave when trained on OpenFWI, a collection of large-scale, multi-structural, …

abstract arxiv big big data boost cs.lg data data-driven deep learning eess.sp impact paper performance physics.geo-ph scale solve study tasks type while

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