Another class of extensions of MIXUP which has been growing in the vision community attempts to fuse raw input image pairs together into a single input image, rather than improve the continuous interpolation mechanism.

Discrete Mix-Up Method

It mixes data and labels of real samples in the exact same way to create more available data.

University of Michigan - Ann Arbor

Data augmentation in data analysis are techniques used to increase the amount of data by adding slightly modified copies of already existing data or newly created synthetic data from existing data. 

Data Augmentation

https://arxiv-download.xixiaoyao.cn/pdf/2105.03075.pdf

A Survey of Data Augmentation Approaches for NLP

Data augmentation (DA) refers to strategies for increasing the diversity of training examples without explicitly collecting new data. Related methods are first explored in computer vision (CV), and DA’s adaptation for natural language processing (NLP) seems secondary and comparatively underexplored.

Data Augmentation in NLP

Rule-based data augmentation is to apply basic changes to the dataset which enlarges the divergence that the neural network sees.

Rule-based Data Augmentation

Interpolation is the process of estimating unknown values that fall between known values.

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