Toward a General Framework for Microarray Data Comparison. - Daniel K. Park; Xiong Wang (CIT, 2006)

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)

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)

Quantum Error Mitigation With Artificial Neural Network. - Changjun Kim; Kyungdeock Daniel Park; June-Koo Kevin Rhee (IEEE Access, 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-classical reinforcement learning for decoding noisy classical parity information. - Kyungdeock Daniel Park; Jonghun Park; June-Koo Kevin Rhee (Quantum Mach. Intell., 2020)

Robust quantum classifier with minimal overhead. - Daniel K. Park; Carsten Blank; Francesco Petruccione (IJCNN, 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)

Linear-depth quantum circuits for multi-qubit controlled gates. - Adenilton J. da Silva; Daniel K. Park (CoRR, 2022)

Variational Quantum Approximate Support Vector Machine With Inference Transfer. - Siheon Park; Daniel K. Park; June-Koo Kevin Rhee (CoRR, 2022)

Architecture representations for quantum convolutional neural networks. - Matt Lourens; Ilya Sinayskiy; Daniel K. Park; Carsten Blank; Francesco Petruccione (CoRR, 2022)

Quantum convolutional neural network for classical data classification. - Tak Hur; Leeseok Kim; Daniel K. Park (Quantum Mach. Intell., 2022)

Neural Quantum Embedding: Pushing the Limits of Quantum Supervised Learning. - Tak Hur; Israel F. Araujo; Daniel K. Park (CoRR, 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., 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., 2023)

Variational quantum one-class classifier. - Gunhee Park; Joonsuk Huh; Daniel K. Park (Mach. Learn. Sci. Technol., 2023)

Classical-to-quantum convolutional neural network transfer learning. - Juhyeon Kim; Joonsuk Huh; Daniel K. Park (Neurocomputing, 2023)

Scalable quantum measurement error mitigation via conditional independence and transfer learning. - Changwon Lee; Daniel K. Park (Mach. Learn. Sci. Technol., 2023)

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)

Expressivity of deterministic quantum computation with one qubit. - Yujin Kim; Daniel K. Park (CoRR, 2024)

Understanding Generalization in Quantum Machine Learning with Margins. - Tak Hur; Daniel K. Park (CoRR, 2024)

Schmidt quantum compressor. - Israel F. Araujo; Hyeondo Oh; Nayeli A. Rodríguez-Briones; Daniel K. Park (CoRR, 2024)

Quantum variational distance-based centroid classifier. - Nicolas M. de Oliveira; Daniel K. Park; Israel F. Araujo; Adenilton J. da Silva (Neurocomputing, 2024)

Quantum support vector data description for anomaly detection. - Hyeondo Oh; Daniel K. Park (Mach. Learn. Sci. Technol., 2024)

Early-stage detection of cognitive impairment by hybrid quantum-classical algorithm using resting-state functional MRI time-series. - Junggu Choi; Tak Hur; Daniel K. Park; Na-Young Shin; Seung-Koo Lee; Hakbae Lee; Sanghoon Han (Knowl. Based Syst., 2025)

Improving Quantum Machine Learning via Heat-Bath Algorithmic Cooling. - Nayeli A. Rodríguez-Briones; Daniel K. Park (CoRR, 2025)

Hamiltonian formulations of centroid-based clustering. - Myeonghwan Seong; Daniel K. Park (CoRR, 2025)