collaborators

25 papers

quant-ph2026

Quasi-polar Decomposition of Quantum Neural Networks via Adaptive Non-local Observables

Shih-Hao Ho, Yan Li, Huan-Hsin Tseng +3

The paper proposes a Diagonal Adaptive Non‑local Observables (DANO) framework that decomposes variational quantum circuit observables into diagonal spectra and unitary bases, treat…

quant-ph2026

Quantum Transformer BSDE Solver via Multi-Layer Fully-Connected Variational Quantum Circuits

Howard Su, Huan-Hsin Tseng, Chi-Sheng Chen +1

Solving high-dimensional parabolic partial differential equations (PDEs) is important in engineering, physics, and stochastic control. Deep BSDE methods reformulate semilinear PDEs…

quant-ph2026

Multivariate Time Series Forecasting with Adaptive Non-Local Observables

Yu-Ting Lee, Huan-Hsin Tseng, Samuel Yen-Chi Chen

Multivariate time series forecasting (MTSF) predicts future values of multiple variables from historical data. While quantum neural networks have been increasingly applied to this…

quant-ph2026

Observable Geometry for Effective Quantum Circuits

Huan-Hsin Tseng, Hsin-Yi Lin, Samuel Yen-Chi Chen +3

We study redundancy and effectiveness of Variational Quantum Circuits via algebraic and geometric views of Lie groups. Considering unitary transformations acting on Hermitian obser…

quant-ph2026

Stable Self-Modulating Quantum Fast-Weight Programmers with Bounded Memory Gates

Kuo-Chung Peng, Jiun-Cheng Jiang, Chun-Hua Lin +8

Quantum Fast-Weight Programmers (QFWPs) store temporal information in dynamically programmed variational-circuit parameters rather than in nonlinear recurrent hidden states, offeri…

quant-ph2026

Self-Modulating Quantum Fast-Weight Programmers for Efficient Adaptive Sequential Learning

Samuel Yen-Chi Chen, Yifeng Peng, Kuo-Chung Peng +8

Recent advances in quantum machine learning have motivated efficient models for sequential data processing. In this paper, we propose Self-Modulating Quantum Fast Weight Programmer…