This repository offers a curated collection of annotated research papers, primarily focused on Machine Learning and Computer Vision. It aims to make complex research papers more accessible and understandable for students, ML engineers, and researchers by providing personal annotations and links to code implementations.

How It Works

The project serves as a personal knowledge base and learning resource. The author annotates papers they find valuable, offering insights and explanations to simplify complex concepts. Each entry typically includes a link to the paper's abstract and, where available, a link to its code implementation, facilitating a deeper understanding and practical exploration of the research.

Quick Start & Requirements

• No installation is required; the repository is a collection of annotated papers.
• Access to the internet is needed to view the papers and associated code.
• Links to official quick-start guides or demos are not applicable as this is a static collection.

Highlighted Details

• Comprehensive coverage across various ML fields including Computer Vision, NLP, Diffusion Models, GANs, and MLLMs.
• Annotations are provided by the repository owner, with guidelines for community contributions to maintain consistency.
• Many entries include direct links to the corresponding code repositories for practical application.
• Papers are organized by field and category, with a focus on papers deemed "interesting" and "useful" by the author.

Maintenance & Community

The repository is maintained by AakashKumarNain. Community contributions are welcomed, with guidelines provided to ensure annotation quality and consistency.

Licensing & Compatibility

The repository itself does not specify a license. The licensing of the individual research papers and their associated code would be governed by their respective licenses. Users should verify compatibility for commercial or closed-source use.

Limitations & Caveats

The annotations are personal interpretations and may not represent the definitive understanding of the papers. The author cannot verify the quality of community-contributed annotations. The repository's organization is based on the author's personal workflow and may not strictly follow chronological order.