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Found 5 papers, 2 papers with code
Improved impedance inversion by deep learning and iterated graph Laplacian
We present a hybrid method that combines deep learning with iterated graph Laplacian and show its application in acoustic impedance inversion which is a routine procedure in seismic explorations.
A Robust Super-resolution Gridless Imaging Framework for UAV-borne SAR Tomography
This paper presents an innovative gridless 3-D imaging framework tailored for UAV-borne TomoSAR.
Semi-supervised Impedance Inversion by Bayesian Neural Network Based on 2-d CNN Pre-training
Seismic impedance inversion can be performed with a semi-supervised learning algorithm, which only needs a few logs as labels and is less likely to get overfitted.
Systematic vector solitary waves from their linear limits in one-dimensional $n$-component Bose-Einstein condensates
We systematically construct a series of vector solitary waves in harmonically trapped one-dimensional three-, four-, and five-component Bose-Einstein condensates.
Quantum Gases Pattern Formation and Solitons
Deep learning for denoising
We use a convolutional neural network as the basic tool for deep learning.
