bgflow | Boltzmann Generators and Normalizing Flows in PyTorch
kandi X-RAY | bgflow Summary
kandi X-RAY | bgflow Summary
bgflow is a Jupyter Notebook library. bgflow has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
Bgflow is a pytorch framework for Boltzmann Generators (BG) and other sampling methods. Boltzmann Generators use neural networks to learn a coordinate transformation of the complex configurational equilibrium distribution to a distribution that can be easily sampled. Accurate computation of free-energy differences and discovery of new configurations are demonstrated, providing a statistical mechanics tool that can avoid rare events during sampling without prior knowledge of reaction coordinates. -- Noe et al. (2019). This library is alpha software under active development. Certain elements of its API are going to change in the future and some current implementations may not be tested. If you are interested in contributing to the library, please feel free to open a pull request or report an issue. When using bgflow in your research, please cite our preprint (coming soon). Implementation of a BG with a single Real NVP coupling block as the invertible transformation. The two-dimensional target potential is given by a double well potential in one dimension and a harmonic potential in the other. The prior distribution is a two-dimensional standard normal distribution. Note that the training procedure is not included in this example.
Bgflow is a pytorch framework for Boltzmann Generators (BG) and other sampling methods. Boltzmann Generators use neural networks to learn a coordinate transformation of the complex configurational equilibrium distribution to a distribution that can be easily sampled. Accurate computation of free-energy differences and discovery of new configurations are demonstrated, providing a statistical mechanics tool that can avoid rare events during sampling without prior knowledge of reaction coordinates. -- Noe et al. (2019). This library is alpha software under active development. Certain elements of its API are going to change in the future and some current implementations may not be tested. If you are interested in contributing to the library, please feel free to open a pull request or report an issue. When using bgflow in your research, please cite our preprint (coming soon). Implementation of a BG with a single Real NVP coupling block as the invertible transformation. The two-dimensional target potential is given by a double well potential in one dimension and a harmonic potential in the other. The prior distribution is a two-dimensional standard normal distribution. Note that the training procedure is not included in this example.
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bgflow has a low active ecosystem.
It has 87 star(s) with 24 fork(s). There are 7 watchers for this library.
It had no major release in the last 6 months.
There are 11 open issues and 6 have been closed. On average issues are closed in 31 days. There are 9 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of bgflow is 0.3.0
Quality
bgflow has no bugs reported.
Security
bgflow has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
bgflow is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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bgflow releases are not available. You will need to build from source code and install.
Installation instructions are not available. Examples and code snippets are available.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of bgflow
bgflow Key Features
No Key Features are available at this moment for bgflow.
bgflow Examples and Code Snippets
No Code Snippets are available at this moment for bgflow.
Community Discussions
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Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install bgflow
You can download it from GitHub.
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For any new features, suggestions and bugs create an issue on GitHub.
If you have any questions check and ask questions on community page Stack Overflow .
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