GiggleLiu/marburg
physics meets neural networks
This project provides hands-on examples for applying deep learning techniques to problems in quantum many-body physics. It demonstrates how neural networks can be used for tasks like sampling, image restoration, and representing quantum wave functions. It's intended for physicists, researchers, and students interested in the intersection of deep learning and quantum physics.
104 stars. No commits in the last 6 months.
Use this if you are a physicist or researcher looking for practical examples to understand how deep learning can be applied to quantum many-body problems, especially for sampling or wave function ansatz.
Not ideal if you are primarily interested in general deep learning applications outside of quantum physics, or if you are looking for a fully-fledged library rather than educational examples.
Stars
104
Forks
33
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Nov 23, 2018
Commits (30d)
0
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