125 citations · 156 across the 4 of their papers we have counts for
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cs.LG2023★ 1 cited
Fourier-DeepONet: Fourier-enhanced deep operator networks for full waveform inversion with improved accuracy, generalizability, and robustness
Min Zhu, Shihang Feng, Youzuo Lin +1
Full waveform inversion (FWI) infers the subsurface structure information from seismic waveform data by solving a non-convex optimization problem. Data-driven FWI has been increasi…
cs.LG2022★ 125 cited
Reliable extrapolation of deep neural operators informed by physics or sparse observations
Min Zhu, Handi Zhang, Anran Jiao +2
Deep neural operators can learn nonlinear mappings between infinite-dimensional function spaces via deep neural networks. As promising surrogate solvers of partial differential equ…
cs.LG2022★ 26 cited
ZLPR: A Novel Loss for Multi-label Classification
Jianlin Su, Mingren Zhu, Ahmed Murtadha +3
In the era of deep learning, loss functions determine the range of tasks available to models and algorithms. To support the application of deep learning in multi-label classificati…