Machine Learning and Statistical Physics
This repository aims to document the reports presented during the 2023 summer school on Machine Learning and Statistical Physics at YNU. It encompasses:
- Comprehensive notes on various talks
- Code examples for selected topics
- Introductions to the speakers
The repository is intended to serve as a platform for sharing and communication among students and teachers working in this field. We hope to update it regularly in the future.
How to contribute
If you would like to contribute to this repository, please follow the steps below:
- Fork this repository to your own account
- Clone the forked repository to your local machine
- Create a new branch for your contribution
- Make your changes and commit them
- Push the changes to your forked repository
- Create a pull request to the original repository
Note: For people not familiar with Git, you can try complete the above steps using the GitHub web interface. (Try out the Codespaces feature where you can edit this online in a virtual environment!)
Thanks
As a student, I would like to express my deep gratitude to all the teachers who put together this extraordinary event. Their hard work and dedication have made this summer school on Machine Learning and Statistical Physics possible. I would also like to thank my classmates for being a constant source of inspiration and for creating a friendly and supportive environment.
I am truly grateful for the knowledge and experiences gained during this summer school, and I eagerly look forward to the chance of meeting all of you again in the future. Thank you for making this an unforgettable learning journey!