Quantum enhanced self supervised learning
Lead Research Organisation:
University of Oxford
Department Name: Oxford Chemistry
Abstract
This project will contribute to QCS WP9 Algorithms with strong links to WP8 Architectures, Control and
Emulation. The research in WP9 investigates how next generation NISQ devices could be used to solve
industrially relevant problems and how they can be interfaced with classical data sources. This project is
concerned with hybrid quantum-classical machine learning networks for solving classification and decision
problems and will utilize state-of-the-art self-supervised learning (SSL) algorithms [arXiv:2002.05709]. SSL
has the great advantage of working with unclassified data but requires a lot more resources than
corresponding supervised algorithms
Emulation. The research in WP9 investigates how next generation NISQ devices could be used to solve
industrially relevant problems and how they can be interfaced with classical data sources. This project is
concerned with hybrid quantum-classical machine learning networks for solving classification and decision
problems and will utilize state-of-the-art self-supervised learning (SSL) algorithms [arXiv:2002.05709]. SSL
has the great advantage of working with unclassified data but requires a lot more resources than
corresponding supervised algorithms
Organisations
People |
ORCID iD |
| Oliver Chapman (Student) |
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/T517811/1 | 30/09/2020 | 29/09/2025 | |||
| 2607531 | Studentship | EP/T517811/1 | 30/09/2021 | 31/12/2025 | Oliver Chapman |