69 citations · 113 across the 11 of their papers we have counts for
11 papers
A Quantum-Classical Collaborative Training Architecture Based on Quantum State Fidelity
Ryan L'Abbate, Anthony D'Onofrio, Samuel Stein +5
Recent advancements have highlighted the limitations of current quantum systems, particularly the restricted number of qubits available on near-term quantum devices. This constrain…
Distributed Quantum Learning with co-Management in a Multi-tenant Quantum System
Anthony D'Onofrio, Amir Hossain, Lesther Santana +5
The rapid advancement of quantum computing has pushed classical designs into the quantum domain, breaking physical boundaries for computing-intensive and data-hungry applications.…
VENUS: A Geometrical Representation for Quantum State Visualization
Shaolun Ruan, Ribo Yuan, Qiang Guan +6
Visualizations have played a crucial role in helping quantum computing users explore quantum states in various quantum computing applications. Among them, Bloch Sphere is the widel…
QuCNN : A Quantum Convolutional Neural Network with Entanglement Based Backpropagation
Samuel A. Stein, Ying Mao, James Ang +1
Quantum Machine Learning continues to be a highly active area of interest within Quantum Computing. Many of these approaches have adapted classical approaches to the quantum settin…
Iterative Qubits Management for Quantum Index Searching in a Hybrid System
Wenrui Mu, Ying Mao, Long Cheng +3
Recent advances in quantum computing systems attract tremendous attention. Commercial companies, such as IBM, Amazon, and IonQ, have started to provide access to noisy intermediate…
VACSEN: A Visualization Approach for Noise Awareness in Quantum Computing
Shaolun Ruan, Yong Wang, Weiwen Jiang +2
Quantum computing has attracted considerable public attention due to its exponential speedup over classical computing. Despite its advantages, today's quantum computers intrinsical…
QuClassi: A Hybrid Deep Neural Network Architecture based on Quantum State Fidelity
Samuel A. Stein, Betis Baheri, Daniel Chen +5
In the past decade, remarkable progress has been achieved in deep learning related systems and applications. In the post Moore's Law era, however, the limit of semiconductor fabric…
Quantum-Inspired Classical Algorithm for Slow Feature Analysis
Daniel Chen, Yekun Xu, Betis Baheri +5
Recently, there has been a surge of interest for quantum computation for its ability to exponentially speed up algorithms, including machine learning algorithms. However, Tang sugg…
A Hybrid System for Learning Classical Data in Quantum States
Samuel A. Stein, Ryan L'Abbate, Wenrui Mu +6
Deep neural network powered artificial intelligence has rapidly changed our daily life with various applications. However, as one of the essential steps of deep neural networks, tr…
Quantum-Inspired Classical Algorithm for Principal Component Regression
Daniel Chen, Yekun Xu, Betis Baheri +4
This paper presents a sublinear classical algorithm for principal component regression. The algorithm uses quantum-inspired linear algebra, an idea developed by Tang. Using this te…
QuGAN: A Quantum State Fidelity based Generative Adversarial Network
Samuel A. Stein, Betis Baheri, Daniel Chen +5
Tremendous progress has been witnessed in artificial intelligence where neural network backed deep learning systems have been used, with applications in almost every domain. As a r…