This repository is a growing collection of concise and focused implementations of research papers across various topics in machine learning / deep learning implemented in PyTorch. Each subdirectoy contains the code of the respective paper/model along with minimal working examples on toy datasets. Rather than aiming for exact architectural or hyperparameter replication, my focus is on understanding and conveying the core insights of each paper in a clean and accessible way.

If you are looking for something similar with deeper annotated implementations, check out: Annotated Deep Learning Paper Implementations

I'm continuously learning and building. Suggestions, issues, and ideas are welcome!