The Expressive Power of Restricted QML Architectures
Offered By: Xanadu via YouTube
Course Description
Overview
Explore the expressive power of restricted Quantum Machine Learning (QML) architectures in this insightful conference talk delivered by Eric Anschuetz, an NSF Graduate Fellow at MIT, during QHack 2023. Delve into the intricacies of QML as Anschuetz shares his expertise on how limitations in quantum architectures can impact their capabilities and potential applications. Gain valuable insights into the cutting-edge research being conducted at the intersection of quantum computing and machine learning, and discover how these restricted architectures may shape the future of quantum technologies.
Syllabus
Eric Anschuetz: The Expressive Power of Restricted QML Architectures | QHack 2023
Taught by
Xanadu
Related Courses
Quantum Information Science II: Efficient Quantum Computing - fault tolerance and complexityMassachusetts Institute of Technology via edX Physical Basics of Quantum Computing
Saint Petersburg State University via Coursera Fundamentals of Quantum Information
Delft University of Technology via edX QC101 Quantum Computing & Intro to Quantum Machine Learning
Udemy Quantum Computing with Qiskit Ultimate Masterclass
Udemy