7 papers · 1 filter
Complementary Matrix-Gated QKAN Fast-Weight Programmers for Quantum Dynamics Forecasting
Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang +14
Sequence models must decide what to write into memory and what to retain. In quantum and quantum-inspired sequence learning, nonlinear recurrent updates often require repeated circ…
Rethinking Quantum Continual Learning with Quantum Fisher Information
Yu-Chao Hsu, Yu-Cheng Lin, Tai-Yue Li +2
Quantum continual learning aims to train quantum models on sequential tasks without losing previously learned knowledge. However, variational quantum classifiers (VQCs) are prone t…
Rank-Refined Quantum-Behaved Particle Swarm Optimization for Quantum Molecular Generation
Sing-Yun Wu, Sheng Yun Wu, I-Min Chiang +1
This work proposes Rank-Refined Quantum-Behaved Particle Swarm Optimization (RR-QPSO) for high-dimensional parameter search in Quantum Molecular Generation (QMG). RR-QPSO targets t…
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…
MPM-QIR: Measurement-Probability Matching for Quantum Image Representation and Compression via Variational Quantum Circuit
Chong-Wei Wang, Mei Ian Sam, Tzu-Ling Kuo +2
We present MPM-QIR, a variational-quantum-circuit (VQC) framework for classical image compression and representation whose core objective is to achieve equal or better reconstructi…
Iterative Matrix Product State Simulation for Scalable Grover's Algorithm
Mei Ian Sam, Tzu-Ling Kuo, Tai-Yue Li
Grover's algorithm is a cornerstone of quantum search algorithm, offering quadratic speedup for unstructured problems. However, limited qubit counts and noise in today's noisy inte…