10 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…
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…
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…
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…