Statistical Modeling: The Two Cultures is an influential essay by Leo Breiman that delineates two approaches to statistical modeling: the "data modeling" culture, which emphasizes formal statistical inference and model fitting, and the "algorithmic modeling" culture, which prioritizes predictive accuracy and computational efficiency. Breiman argues for a shift towards the latter culture, advocating for the development and use of robust algorithms and machine learning techniques that focus on prediction rather than solely on theoretical statistical inference.

Paper exploration on SMOTE, or Synthetic Minority Over-sampling Technique, which was introduced to tackle class imbalance. Currently, it is widely adopted by practitioners and researchers alike.

An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale: An exploration on how ViT can be used for vision.