COVID-19 AI Quantum Tensorflow is a Peter Moss COVID-19 AI Research Project Artificial Intelligence & Quantum Technologies research and development project using Tensorflow Quantum.
This repository will provide several projects created by our team. Projects include installation scripts, documentation and code for Quantum AI algorithms built for fighting and understanding COVID-19.
The Peter Moss COVID-19 AI Research Project is a Peter Moss Leukemia AI Research project. Our goal is to keep our research and technology open-source and free.
"TensorFlow Quantum (TFQ) is a quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models. Research in quantum algorithms and applications can leverage Google’s quantum computing frameworks, all from within TensorFlow.
TensorFlow Quantum focuses on quantum data and building hybrid quantum-classical models. It integrates quantum computing algorithms and logic designed in Cirq, and provides quantum computing primitives compatible with existing TensorFlow APIs, along with high-performance quantum circuit simulators. Read more in the TensorFlow Quantum white paper." Source:
Please follow the Installation Guide to install COVID-19 AI Quantum Tensorflow. Each project shown below may have it's own additional installation guide.
Below are the current projects.
| ID | Project | Description | Author |
|---|---|---|---|
| 1 | Leveraging Quantum MNIST to detect COVID-19 | A COVID-19 QNN (Quantum Neural Network) classification project based on the Tensorflow Quantum MNIST Classification | Adam Milton-Barker |
The Peter Moss COVID-19 AI Research Project encourages, and welcomes, code contributions, bug fixes and enhancements from the Github.
Please read the CONTRIBUTING document for a full guide to forking our repositories and submitting your pull requests. You will also find information about our code of conduct on this page.
- Adam Milton-Barker - Peter Moss Leukemia AI Research Founder & Intel Software Innovator, Sabadell, Spain
We use SemVer for versioning. For the versions available, see Releases.
This project is licensed under the MIT License - see the LICENSE file for details.
We use the repo issues to track bugs and general requests related to using this project. See CONTRIBUTING for more info on how to submit bugs, feature requests and proposals.