Quantum and Physics Based Machine Learning
Directors
Fellows & Scholars
The aim of the Ellis program Quantum and Physics based machine learning (QPhML) is to use concepts from quantum physics and statistical physics to develop novel machine learning algorithms with the ultimate aim to realize novel future, possibly energy efficient, hardware implementations. Objectives:
- Exploit quantum effects in machine learning
- Accelerate and improve energy efficiency of machine learning algorithms through dedicated physical implementations
- Use machine learning methods to advance understanding of quantum information processing
