69 citations · 100 across the 9 of their papers we have counts for
9 papers
Approximate Quantum Circuit Cutting
Daniel Chen, Betis Baheri, Vipin Chaudhary +3
Current and imminent quantum hardware lacks reliability and applicability due to noise and limited qubit counts. Quantum circuit cutting -- a technique dividing large quantum circu…
QuFI: a Quantum Fault Injector to Measure the Reliability of Qubits and Quantum Circuits
Daniel Oliveira, Edoardo Giusto, Emanuele Dri +5
Quantum computing is a new technology that is expected to revolutionize the computation paradigm in the next few years. Qubits exploit the quantum physics proprieties to increase t…
A Systematic Methodology to Compute the Quantum Vulnerability Factors for Quantum Circuits
Daniel Oliveira, Edoardo Giusto, Betis Baheri +3
Quantum computing is one of the most promising technology advances of the latest years. Once only a conceptual idea to solve physics simulations, quantum computation is today a rea…
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…
MARS: Malleable Actor-Critic Reinforcement Learning Scheduler
Betis Baheri, Jacob Tronge, Bo Fang +3
In this paper, we introduce MARS, a new scheduling system for HPC-cloud infrastructures based on a cost-aware, flexible reinforcement learning approach, which serves as an intermed…