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quant-ph2026

Complementary Matrix-Gated QKAN Fast-Weight Programmers for Quantum Dynamics Forecasting

Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang +14

The paper proposes Complementary Matrix Gating, a coordinate‑wise gating scheme for fast‑weight programmers built on quantum‑inspired Kolmogorov‑Arnold networks, and shows it impro…

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

Parameter-Efficient Quantum-Inspired Fast Weight Programmers for Traffic-Matrix Forecasting

Kuo-Chung Peng, Jiun-Cheng Jiang, Chun-Hua Lin +3

Traffic matrices (TMs) capture network-wide origin-destination demand and are central to traffic engineering, yet accurate whole-matrix forecasting remains challenging when predict…

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…

quant-ph2026

Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptation

Samuel Yen-Chi Chen, Yifeng Peng, Jiun-Cheng Jiang +8

Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing. In this paper, we propose a Recursive Qua…

quant-ph2026

Generative Quantum-inspired Kolmogorov-Arnold Eigensolver

Yu-Cheng Lin, Yu-Chao Hsu, I-Shan Tsai +9

High-performance computing (HPC) is increasingly important for scalable quantum chemistry workflows that couple classical generative models, quantum circuit simulation, and selecte…