Abstract: This paper proposes a statistical regularization method for deep learning oriented towards robust data mining. By introducing multi-level statistical constraints and adaptive regularization ...
Regularization in Deep Learning is very important to overcome overfitting. When your training accuracy is very high, but test accuracy is very low, the model highly overfits the training dataset set ...
Abstract: The suppression of surface-related multiples has become a critical step in seismic data processing. In fact, the absence of near-offset traces acquisitions significantly compromises the ...
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