18 citations · 30 across the 4 of their papers we have counts for
4 papers
Structure-Aware Variational State Preparation for Quantum Basket Option Pricing
Dongwoo Kim, Zhenyu Cui, Daniel K. Park +1
Basket option pricing often relies on Monte Carlo estimation, for which quantum amplitude estimation (QAE) provides a quadratic speed-up. However, the practical benefit of QAE can…
Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension
Changwon Lee, Israel F. Araujo, Dongha Kim +4
Quantum convolutional neural networks (QCNNs) represent a promising approach in quantum machine learning, paving new directions for both quantum and classical data analysis. This a…
Quantum-inspired classification via efficient simulation of Helstrom measurement
Wooseop Hwang, Daniel K. Park, Israel F. Araujo +1
The Helstrom measurement (HM) is known to be the optimal strategy for distinguishing non-orthogonal quantum states with minimum error. Previously, a binary classifier based on clas…
Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning
Tak Hur, Israel F. Araujo, Daniel K. Park
Quantum embedding is a fundamental prerequisite for applying quantum machine learning techniques to classical data, and has substantial impacts on performance outcomes. In this stu…