4 citations · 12 across the 4 of their papers we have counts for
4 papers
Introduction to Quantum Error Correction with Stabilizer Codes
Zachary P. Bradshaw, Jeffrey J. Dale, Ethan N. Evans
We give an introduction to the theory of quantum error correction using stabilizer codes that is geared towards the working computer scientists and mathematicians with an interest…
Learning Equivariant Maps with Variational Quantum Circuits
Zachary P. Bradshaw, Ethan N. Evans, Matthew Cook +1
Geometric quantum machine learning uses the symmetries inherent in data to design tailored machine learning tasks with reduced search space dimension. The field has been well-studi…
Learning with SASQuaTCh: a Novel Variational Quantum Transformer Architecture with Kernel-Based Self-Attention
Ethan N. Evans, Matthew Cook, Zachary P. Bradshaw +1
The recent exploding growth in size of state-of-the-art machine learning models highlights a well-known issue where exponential parameter growth, which has grown to trillions as in…
A Quick Introduction to Quantum Machine Learning for Non-Practitioners
Ethan N. Evans, Dominic Byrne, Matthew G. Cook
This paper provides an introduction to quantum machine learning, exploring the potential benefits of using quantum computing principles and algorithms that may improve upon classic…