Daniel K. Park

According to our database, Daniel K. Park authored at least 19 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Optimizing Quantum Convolutional Neural Network Architectures for Arbitrary Data Dimension.

Changwon Lee, Israel F. Araujo, Dongha Kim, Junghan Lee, Siheon Park, Ju-Young Ryu, Daniel K. Park

CoRR, 2024

2023

Scalable quantum measurement error mitigation via conditional independence and transfer learning.

Changwon Lee, Daniel K. Park

Mach. Learn. Sci. Technol., December, 2023

Classical-to-quantum convolutional neural network transfer learning.

Juhyeon Kim, Joonsuk Huh, Daniel K. Park

Neurocomputing, October, 2023

Variational quantum one-class classifier.

Gunhee Park, Joonsuk Huh, Daniel K. Park

Mach. Learn. Sci. Technol., March, 2023

Configurable sublinear circuits for quantum state preparation.

Israel F. Araujo, Daniel K. Park, Teresa Bernarda Ludermir, Wilson Rosa de Oliveira, Francesco Petruccione, Adenilton J. da Silva

Quantum Inf. Process., February, 2023

Quantum-inspired algorithm for direct multi-class classification.

Roberto Giuntini, Federico Hernan Holik, Daniel K. Park, Hector Freytes, Carsten Blank, Giuseppe Sergioli

Appl. Soft Comput., February, 2023

Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning.

Tak Hur, Israel F. Araujo, Daniel K. Park

CoRR, 2023

2022

Quantum convolutional neural network for classical data classification.

Tak Hur, Leeseok Kim, Daniel K. Park

Quantum Mach. Intell., 2022

Architecture representations for quantum convolutional neural networks.

Matt Lourens, Ilya Sinayskiy, Daniel K. Park, Carsten Blank, Francesco Petruccione

CoRR, 2022

Variational Quantum Approximate Support Vector Machine With Inference Transfer.

Siheon Park, Daniel K. Park, June-Koo Kevin Rhee

CoRR, 2022

Linear-depth quantum circuits for multi-qubit controlled gates.

Adenilton J. da Silva, Daniel K. Park

CoRR, 2022

2021

Circuit-Based Quantum Random Access Memory for Classical Data With Continuous Amplitudes.

Tiago Mendonça Lucena de Veras, Ismael C. S. de Araujo, Daniel K. Park, Adenilton J. da Silva

IEEE Trans. Computers, 2021

Robust quantum classifier with minimal overhead.

Daniel K. Park, Carsten Blank, Francesco Petruccione

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Quantum-classical reinforcement learning for decoding noisy classical parity information.

Kyungdeock Daniel Park, Jonghun Park, June-Koo Kevin Rhee

Quantum Mach. Intell., 2020

A divide-and-conquer algorithm for quantum state preparation.

Israel F. Araujo, Kyungdeock Daniel Park, Francesco Petruccione, Adenilton J. da Silva

CoRR, 2020

Quantum Error Mitigation With Artificial Neural Network.

Changjun Kim, Kyungdeock Daniel Park, June-Koo Kevin Rhee

IEEE Access, 2020

2016

Erratum to: Hyperfine spin qubits in irradiated malonic acid: heat-bath algorithmic cooling.

Kyungdeock Daniel Park, Guanru Feng, Robabeh Rahimi, Stéphane Labruyère, Taiki Shibata, Shigeaki Nakazawa, Kazunobu Sato, Takeji Takui, Raymond Laflamme, Jonathan Baugh

Quantum Inf. Process., 2016

2015

Hyperfine spin qubits in irradiated malonic acid: heat-bath algorithmic cooling.

Kyungdeock Daniel Park, Guanru Feng, Robabeh Rahimi, Stéphane Labruyère, Taiki Shibata, Shigeaki Nakazawa, Kazunobu Sato, Takeji Takui, Raymond Laflamme, Jonathan Baugh

Quantum Inf. Process., 2015

2006

Toward a General Framework for Microarray Data Comparison.

Daniel K. Park, Xiong Wang

Proceedings of the Sixth International Conference on Computer and Information Technology (CIT 2006), 2006