8 papers
Margin-Based Generalization for Quantum Machine Learning with Classical Data Encoding
Ju-Young Ryu, Tak Hur, Daniel K. Park
Understanding generalization is essential for assessing the practical viability of quantum machine learning. In many applications, quantum models operate on classical data that mus…
Prototype-Guided Optimization of Quantum Data Embeddings with Linear Cost
Seokhoon Jeong, Daniel K. Park
In supervised quantum machine learning with classical data, classification performance critically depends on the geometry induced by quantum data embedding. Existing data-adaptive…
Machine Learning Approaches to Decoding Topological Quantum Codes
Changwon Lee, Tak Hur, Jeongwoo Jae +1
Decoding is an essential component of quantum error correction (QEC), translating stabilizer measurement outcomes into corrective actions that suppress logical errors and preserve…
Generative Modeling of Quantum Distribution with Functional Flow Matching
Jaehoon Hahm, Tak Hur, Joonseok Lee +1
The emergence of powerful deep generative models based on diffusion and flow matching has enabled the learning and modeling of complex distributions. Learning quantum distributions…
Optimizing Quantum Data Embeddings for Ligand-Based Virtual Screening
Junggu Choi, Tak Hur, Seokhoon Jeong +5
Effective molecular representations are essential for ligand-based virtual screening. We investigate how quantum data embedding strategies can improve this task by developing and e…
Scalable Neural Decoders for Practical Real-Time Quantum Error Correction
Changwon Lee, Tak Hur, Daniel K. Park
Real-time, scalable, and accurate decoding is a critical component for realizing a fault-tolerant quantum computer. While Transformer-based neural decoders such as \textit{AlphaQub…
Understanding Generalization in Quantum Machine Learning with Margins
Tak Hur, Daniel K. Park
Understanding and improving generalization capabilities is crucial for both classical and quantum machine learning (QML). Recent studies have revealed shortcomings in current gener…
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 +4
Following the recent development of quantum machine learning techniques, the literature has reported several quantum machine learning algorithms for disease detection. This study e…