no code implementations • 27 May 2024 • Yidong Liao, Xiao-Ming Zhang, Chris Ferrie
This paper proposes frameworks for implementing GNNs on quantum computers to potentially address the challenges.
1 code implementation • 29 Aug 2023 • Gal Weitz, Lirandë Pira, Chris Ferrie, Joshua Combes
Quantum variational circuits have gained significant attention due to their applications in the quantum approximate optimization algorithm and quantum machine learning research.
1 code implementation • 22 Aug 2023 • Lirandë Pira, Chris Ferrie
Here, we explore the interpretability of quantum neural networks using local model-agnostic interpretability measures commonly utilized for classical neural networks.
no code implementations • 14 Nov 2022 • Lirandë Pira, Chris Ferrie
In this review, we consider ideas from distributed deep learning as they apply to quantum neural networks.
no code implementations • 31 Mar 2021 • Yidong Liao, Min-Hsiu Hsieh, Chris Ferrie
Training quantum neural networks (QNNs) using gradient-based or gradient-free classical optimisation approaches is severely impacted by the presence of barren plateaus in the cost landscapes.