47 citations · 116 across the 6 of their papers we have counts for
5 papers · 1 filter
Decohering Tensor Network Quantum Machine Learning Models
Haoran Liao, Ian Convy, Zhibo Yang +1
Tensor network quantum machine learning (QML) models are promising applications on near-term quantum hardware. While decoherence of qubits is expected to decrease the performance o…
A Logarithmic Bayesian Approach to Quantum Error Detection
Ian Convy, K. Birgitta Whaley
We consider the problem of continuous quantum error correction from a Bayesian perspective, proposing a pair of digital filters using logarithmic probabilities that are able to ach…
Machine Learning for Continuous Quantum Error Correction on Superconducting Qubits
Ian Convy, Haoran Liao, Song Zhang +5
Continuous quantum error correction has been found to have certain advantages over discrete quantum error correction, such as a reduction in hardware resources and the elimination…
Mutual Information Scaling for Tensor Network Machine Learning
Ian Convy, William Huggins, Haoran Liao +1
Tensor networks have emerged as promising tools for machine learning, inspired by their widespread use as variational ansatze in quantum many-body physics. It is well known that th…
Robust in Practice: Adversarial Attacks on Quantum Machine Learning
Haoran Liao, Ian Convy, William J. Huggins +1
State-of-the-art classical neural networks are observed to be vulnerable to small crafted adversarial perturbations. A more severe vulnerability has been noted for quantum machine…