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XanaduAI / QHack2021

Official repo for QHack—the quantum machine learning hackathon
https://qhack.ai
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[ENTRY] Hybrid quantum-classical neural networks for self-driving cars #52

Open DenisKatic opened 3 years ago

DenisKatic commented 3 years ago

Team Name:

DK02

Project Description:

This project aims to test and evaluate the current capabilities of variational quantum circuits based on a hybrid ML approach, and a simplified and simulated version of a self-driving use case.

The idea is to train a classic ML model that contains multiple CNN and dense layers to predict the car's steering angle based on images. After a good model has been successfully trained, some of the weights are transferred (transfer learning) to a new model architecture, where a dense layer has been exchanged for a variational quantum circuit. Only the weights and parameters that have not been transferred are trained. Furthermore, various quantum circuits are trained and evaluated.

Presentation:

https://github.com/DenisKatic/SelfDrivingQuantumHybrid/blob/main/documents/QHack_2021_DK02.pdf

Source code:

https://github.com/DenisKatic/SelfDrivingQuantumHybrid

co9olguy commented 3 years ago

Thanks for the submission! We hope you have enjoyed participating in QHack :smiley:

We will be assessing the entries and contacting the winners separately. Winners will be publicly announced sometime in the next month.

We will also be freezing the GitHub repo as we sort through the submitted projects, so you will not be able to update this submission.