Bibliography (9):

1. Attention Is All You Need

2. MLP-Mixer: An all-MLP Architecture for Vision

3. Sharpness-Aware Minimization (SAM) for Efficiently Improving Generalization

4. Contrastive Representation Learning: A Framework and Review

5. ImageNet Large Scale Visual Recognition Challenge

6. Vision Transformer: An Image is Worth 16×16 Words: Transformers for Image Recognition at Scale

7. Deep Residual Learning for Image Recognition

8. https://github.com/google-research/vision_transformer

9. Wikipedia Bibliography:

   1. Data augmentation