14 citations · 24 across the 8 of their papers we have counts for
9 papers
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…
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…
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…
Financial Vision Based Reinforcement Learning Trading Strategy
Yun-Cheng Tsai, Fu-Min Szu, Jun-Hao Chen +1
Recent advances in artificial intelligence (AI) for quantitative trading have led to its general superhuman performance in significant trading performance. However, the potential r…
Dynamic Deep Convolutional Candlestick Learner
Jun-Hao Chen, Yun-Cheng Tsai
Candlestick pattern is one of the most fundamental and valuable graphical tools in financial trading that supports traders observing the current market conditions to make the prope…
Financial Vision Based Differential Privacy Applications
Jun-Hao Chen, Yi-Jen Wang, Yun-Cheng Tsai +1
The importance of deep learning data privacy has gained significant attention in recent years. It is probably to suffer data breaches when applying deep learning to cryptocurrency…