Welcome to my collection of notes and blogs on topics that I find fascinating and impactful in the world of research! This repository is a curated compilation of my study notes, personal insights, and blog posts covering cutting-edge research papers, classic literature, and foundational theories.
- Generative Models: Insights into state-of-the-art generative modeling techniques, including diffusion models, GANs, VAEs, and more.
- AI4Science: Applications of AI in scientific discovery, including chemistry, biology, materials science, and physics.
- Learning Theory: Concepts, proofs, and commentaries on machine learning theory, generalization, optimization, and statistical learning.
- Mathematics: Mathematical foundations, useful tricks, and explanations relevant to machine learning and theoretical physics.
- Physics: Notes on interesting physics papers and the intersection of AI and physics.
- Statistics: Key concepts, statistical inference, and useful results for research.
- To organize and share notes that helped me understand complex papers and concepts.
- To support fellow researchers and students who are also interested in these topics.
- To encourage discussion and learning within the community.
/notes/ # Paper notes (linked to original papers where possible)
/blog/ # Blog posts on research, trends, and personal insights
/resources/ # Recommended readings, tools, and external links
- Browse by topic or date.
- Feel free to open issues or submit pull requests if you want to discuss something or add your own insights!
- Suggestions and feedback are very welcome.
Special thanks to the amazing researchers whose work I learn from. Please check out the original papers for full details and credit.
MIT β feel free to use, adapt, and share with attribution!
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