Enhancing Polynomial Chaos Expansion Based Surrogate Modeling using a Novel Probabilistic Transfer Learning Strategy

no code implementations • 7 Dec 2023 • Wyatt Bridgman, Uma Balakrishnan, Reese Jones, Jiefu Chen, Xuqing Wu, Cosmin Safta, Yueqin Huang, Mohammad Khalil

For black-box simulations, non-intrusive PCE allows the construction of these surrogates using a set of simulation response evaluations.

regression Transfer Learning

First arrival picking using U-net with Lovasz loss and nearest point picking method

no code implementations • 6 Apr 2021 • Pengyu Yuan, Wenyi Hu, Xuqing Wu, Jiefu Chen, Hien Van Nguyen

Similar to \cite{wu2019semi}, we use U-net to perform the segmentation as it is proven to be state-of-the-art in many image segmentation tasks.

Contour Detection Image Segmentation +2

Progressive transfer learning for low frequency data prediction in full waveform inversion

no code implementations • 20 Dec 2019 • Wenyi Hu, Yuchen Jin, Xuqing Wu, Jiefu Chen

For the purpose of effective suppression of the cycle-skipping phenomenon in full waveform inversion (FWI), we developed a Deep Neural Network (DNN) approach to predict the absent low-frequency components by exploiting the implicit relation connecting the low-frequency and high-frequency data through the subsurface geological and geophysical properties.

Transfer Learning