pyrkm
:zap::zap::zap: Restricted Kirchhoff Machines with python
Science Score: 67.0%
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✓DOI references
Found 7 DOI reference(s) in README -
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○Scientific vocabulary similarity
Low similarity (15.4%) to scientific vocabulary
Repository
:zap::zap::zap: Restricted Kirchhoff Machines with python
Basic Info
- Host: GitHub
- Owner: Kirchhoff-Machines
- License: apache-2.0
- Language: Python
- Default Branch: main
- Homepage: https://kirchhoff-machines.github.io/pyrkm/
- Size: 7.12 MB
Statistics
- Stars: 1
- Watchers: 0
- Forks: 0
- Open Issues: 0
- Releases: 2
Metadata Files
README.md
What is a Restricted Kirchhoff Machine?
You may be familiar with Restricted Boltzmann Machines (RBMs) [1]-[2], which are a type of generative neural network that can learn a probability distribution over its input data. The Restricted Kirchhoff Machine (RKM) is a realization of a RBM using resistor networks, and Kirchhoff's laws of electrical circuits. In this repository, we provide a Python package to virtually simulate the training and evaluation of RKMs.
For more information about the capabilities of the RKM, see the original paper by Link to paper XXXX.
Repository Contents
In this repository you will find the following:
src/pyrkm/: The main package code. You can use this code to train and evaluate RKMs. For more information, see the documentation. For a quick start, see the Usage section below.energy_consumption: A series of scripts to evaluate the energy consumption of the RKM and compare it to the estimated cost of a RBM. They are used to generate the results in the paper XXX.
Getting Started
To get started with the project, follow these steps:
Prerequisites: In order to correctly install
pyrkmyou needpython3.9or higher. If you don't have it installed, you can download it from the official website.Install the package:
bash python -m pip install pyrkmOr: Clone the repository:
bash git clone https://github.com/Kirchhoff-Machines/pyrkm.git cd pyrkm git submodule init git submodule update pip install .
Usage
To learn how to use the package, follow the official documentation and in particular this tutorial.
Contribution Guidelines
We welcome contributions to improve and expand the capabilities of this project. If you have ideas, bug fixes, or enhancements, please submit a pull request. Check out our Contributing Guidelines to get started with development.
Generative-AI Disclaimer
Parts of the code have been generated and/or refined using GitHub Copilot. All AI-output has been verified for correctness, accuracy and completeness, revised where needed, and approved by the author(s).
How to cite
Please consider citing this software that is published in Zenodo under the DOI 10.5281/zenodo.14865380.
License
This project is licensed under the Apache 2.0 License - see the LICENSE file for details.
Owner
- Name: Kirchhoff-Machines
- Login: Kirchhoff-Machines
- Kind: organization
- Repositories: 1
- Profile: https://github.com/Kirchhoff-Machines
Citation (CITATION.cff)
# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!
cff-version: 0.0.8
title: pyrkm
message: >-
If you use this software, please cite it using the
metadata from this file.
type: software
authors:
- given-names: Simone
family-names: Ciarella
email: simoneciarella@gmail.com
affiliation: Netherlands eScience Center
orcid: 'https://orcid.org/0000-0002-9247-139X'
- given-names: Marcelo
family-names: Guzmán
affiliation: University of Pennsylvania
orcid: 'https://orcid.org/0000-0002-5256-8840'
repository-code: 'https://github.com/Kirchhoff-Machines/pyrkm'
url: 'https://pyrkm.readthedocs.io'
abstract: >-
Machines learning to do machine-learning
keywords:
- machine learning
- boltzmann machine
- physical learning
- equilibrium propagation
license: Apache-2.0
version: 0.0.8
GitHub Events
Total
- Create event: 3
- Issues event: 2
- Release event: 2
- Watch event: 2
- Public event: 1
- Push event: 25
- Pull request event: 2
Last Year
- Create event: 3
- Issues event: 2
- Release event: 2
- Watch event: 2
- Public event: 1
- Push event: 25
- Pull request event: 2
Packages
- Total packages: 1
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Total downloads:
- pypi 33 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 8
- Total maintainers: 1
pypi.org: pyrkm
Machines learning to do machine-learning
- Documentation: https://pyrkm.readthedocs.io/
- License: Apache 2.0 License
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Latest release: 0.0.8
published about 1 year ago