arXiv:2607. 16358v1 Announce Type: cross Abstract: This paper presents a unified quantum-classical hybrid framework for multi-horizon time-series forecasting, introducing two model variants Quantum Reservoir Forecaster (QRC-F) and Variational Quantum Forecaster (VQF-F).
By Sanjay Chakraborty, Fredrik Heintz
The paper introduces a recursive quantum long short-term memory (QLSTM) architecture and compares it to a standard QLSTM for one-step-ahead daily temperature forecasting. Using Toronto weather data and identical training settings, the recursive model consistently reaches near-optimal test loss earlier, achieves lower mean absolute error and root mean squared error, and shows a smaller generalization gap across input windows of 8, 16, and 32 days over 20 random seeds. These findings suggest that recursive quantum feature transformations can enhance stability and out-of-sample performance in compact hybrid quantum–classical temporal models.
By Mu-En Lee, Yen-Ku Liu, Samuel Yen-Chi Chen, Yun-Cheng Tsai
arXiv:2504. 20823v3 Announce Type: replace Abstract: Accurate remaining useful life (RUL) estimation underpins safe operation and cost-effective maintenance of aerospace propulsion systems.
By Olga Tsurkan, Aleksandra Konstantinova, Arsenii Senokosov, Asel Sagingalieva, Alexey Melnikov
arXiv:2605. 06734v2 Announce Type: replace-cross Abstract: Fast Weight Programmers (FWPs) encode temporal dependencies through dynamically updated parameters rather than recurrent hidden states.
By Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang, Chen-Yu Liu, En-Jui Kuo, Yun-Yuan Wang, Prayag Tiwari, Andrea Ceschini, Chi-Sheng Chen, Yu-Chao Hsu, Chun-Hua Lin, Tai-Yue Li, Antonello Rosato, Massimo Panella, Simon See, Saif Al-Kuwari, Kuan-Cheng Chen, Nan-Yow Chen, Hsi-Sheng Goan
arXiv:2510.25183v2 Announce Type: replace-cross
Abstract: Energy-efficient AI should be evaluated across the full application pipeline, not only by lowest error or shortest training time. We study th...
By Avyay Kodali, Priyanshi Singh, Pranay Pandey, Krishna Bhatia, Shalini Devendrababu, Srinjoy Ganguly
arXiv:2603. 09789v3 Announce Type: replace-cross Abstract: Accurate financial volatility forecasting is crucial but challenged by the non-linear, highly correlated nature of market data.
By Yixiong Chen