14 papers
Recursive Quantum Long Short-Term Memory for Stable Short-Horizon Temperature Forecasting
Mu-En Lee, Yen-Ku Liu, Samuel Yen-Chi Chen +1
Quantum long short-term memory (QLSTM) models extend recurrent sequence learning with variational quantum circuits, but their optimization behavior can vary substantially across ra…
Titans-QFWP: A Regime-Aware Hybrid Quantum Fast Weight Programmer for Portfolio Optimization
Ming-Kai Hung, Jun-Hao Chen, Yun-Cheng Tsai +1
We propose Titans-QFWP, a hybrid reinforcement learning architecture integrating a Quantum Fast Weight Programmer with Titans-style memory (Persistence, Surprise, and Forgetting) f…
Quantum-Enhanced Temporal Embeddings via a Hybrid Seq2Seq Architecture
Tien-Ching Hsieh, Yun-Cheng Tsai, Samuel Yen-Chi Chen
This work investigates how shallow, NISQ-compatible quantum layers can improve temporal representation learning in real-world sequential data. We develop a QLSTM Seq2Seq autoencode…
Automated Analysis of DFT Output Files for Molecular Descriptor Extraction and Reactivity Modeling
Yu-Chien Huang, Dennis Chung-Yang Huang, Yun-Cheng Tsai
Understanding the relationship between molecular structure and chemical reactivity or properties is fundamental to rational molecular design. Linear free energy relationships (LFER…
Batched Training for QLSTM vs. QFWP: A System-Oriented Approach to EPC-Aware RMSE-DA
Jun-Hao Chen, Ming-Kai Hung, Yun-Cheng Tsai +1
We compare two quantum sequence models, QLSTM and QFWP, under an Equal Parameter Count (EPC) and adjoint differentiation setup on daily EUR USD forecasting as a controlled one dime…
Q-A3C2: Quantum Reinforcement Learning with Time-Series Dynamic Clustering for Adaptive ETF Stock Selection
Yen-Ku Liu, Yun-Cheng Tsai, Samuel Yen-Chi Chen
Traditional ETF stock selection methods and reinforcement learning models such as the Asynchronous Advantage Actor-Critic (A3C) often suffer from high-dimensional feature spaces an…
Enhancing the Practical Reliability of Shor's Quantum Algorithm via Generalized Period Decomposition: Theory and Large-Scale Empirical Validation
Chih-Chen Liao, Chia-Hsin Liu, Yun-Cheng Tsai
This work presents a generalized period decomposition approach, significantly improving the practical reliability of Shor's quantum factoring algorithm. Although Shor's algorithm t…
A Modular AIoT Framework for Low-Latency Real-Time Robotic Teleoperation in Smart Cities
Shih-Chieh Sun, Yun-Cheng Tsai
This paper presents an AI-driven IoT robotic teleoperation system designed for real-time remote manipulation and intelligent visual monitoring, tailored for smart city applications…
Benchmarking Quantum and Classical Sequential Models for Urban Telecommunication Forecasting
Chi-Sheng Chen, Samuel Yen-Chi Chen, Yun-Cheng Tsai
In this study, we evaluate the performance of classical and quantum-inspired sequential models in forecasting univariate time series of incoming SMS activity (SMS-in) using the Mil…
Quantum-Enhanced Forecasting for Deep Reinforcement Learning in Algorithmic Trading
Jun-Hao Chen, Yu-Chien Huang, Yun-Cheng Tsai +1
The convergence of quantum-inspired neural networks and deep reinforcement learning offers a promising avenue for financial trading. We implemented a trading agent for USD/TWD by i…
Quantum-Enhanced Reinforcement Learning with LSTM Forecasting Signals for Optimizing Fintech Trading Decisions
Yen-Ku Liu, Yun-Huei Pan, Pei-Fan Lu +2
Financial trading environments are characterized by high volatility, numerous macroeconomic signals, and dynamically shifting market regimes, where traditional reinforcement learni…
Enhancing Interpretability of Quantum-Assisted Blockchain Clustering via AI Agent-Based Qualitative Analysis
Yun-Cheng Tsai, Yen-Ku Liu, Samuel Yen-Chi Chen
Blockchain transaction data is inherently high dimensional, noisy, and entangled, posing substantial challenges for traditional clustering algorithms. While quantum enhanced cluste…
Robust and Annotation-Free Wound Segmentation on Noisy Real-World Pressure Ulcer Images: Towards Automated DESIGN-R\textsuperscript{\textregistered} Assessment
Yun-Cheng Tsai
Purpose: Accurate wound segmentation is essential for automated DESIGN-R scoring. However, existing models such as FUSegNet, which are trained primarily on foot ulcer datasets, oft…
Quantum Feature Optimization for Enhanced Clustering of Blockchain Transaction Data
Yun-Cheng Tsai, Samuel Yen-Chi Chen
Blockchain transaction data exhibits high dimensionality, noise, and intricate feature entanglement, presenting significant challenges for traditional clustering algorithms. In thi…