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Found 2 papers, 1 papers with code
MixupE: Understanding and Improving Mixup from Directional Derivative Perspective
Mixup is a popular data augmentation technique for training deep neural networks where additional samples are generated by linearly interpolating pairs of inputs and their labels.
Model identification for ARMA time series through convolutional neural networks
In this paper, we use convolutional neural networks to address the problem of model identification for autoregressive moving average time series models.
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