arXiv AI

Controllable Quantum Memory Capacity in Quantum Reservoir Networks with Tunable partial-SWAPs

arXiv:2605. 12713v3 Announce Type: replace-cross Abstract: In the field of quantum reservoir computing (QRC), many different computational models and architectures have been proposed.

arXiv Machine Learning

Jul 22

Quantum Reservoir Computing: Recent Advances and Future Directions

arXiv:2607. 18552v1 Announce Type: cross Abstract: Quantum reservoir computing (QRC) uses the dynamics of a fixed or weakly tuned quantum system to transform temporal and sequential inputs into measured features, while training is typically confined to a classical readout.

By Shehbaz Tariq, Muhammad Talha, Arshid Ali, Muhammad Diyan, Symeon Chatzinotas

benchmarks

arXiv Machine Learning

Jul 21

Multivariate Time Series Forecasting with Gate-Based Quantum Reservoir Computing on NISQ Hardware

arXiv:2510. 13634v2 Announce Type: replace Abstract: Quantum reservoir computing (QRC) offers a hardware-friendly approach to temporal learning, yet most studies target univariate signals and overlook near-term hardware constraints.

By Wissal Hamhoum, Soumaya Cherkaoui, Jean-Frederic Laprade, Ola Ahmad, Shengrui Wang

arXiv Machine Learning

Jun 25

Recursive QLSTM with Dynamic Variational Quantum Circuit Adaptation

arXiv:2606. 24932v1 Announce Type: cross Abstract: Recent advances in quantum computing and machine learning have motivated the development of quantum models for sequential data processing.

By Samuel Yen-Chi Chen, Yifeng Peng, Jiun-Cheng Jiang, Chun-Hua Lin, Kuo-Chung Peng, Junghoon Justin Park, Huan-Hsin Tseng, Hsin-Yi Lin, Kuan-Cheng Chen, Chen-Yu Liu, Shinjae Yoo

arXiv Machine Learning

Jul 31

QAdapt: A Noise-Adaptive Neural Pre-Decoding Framework for Quantum Error Correction

arXiv:2607. 28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale.

By Ran Miao, Rui Luo, Xiaohan Shan, Xiaoming Sun

fine-tuning benchmarks

arXiv AI

Jul 3

Stable Self-Modulating Quantum Fast-Weight Programmers with Bounded Memory Gates

arXiv:2607. 02363v1 Announce Type: cross Abstract: Quantum Fast-Weight Programmers (QFWPs) store temporal information in dynamically programmed variational-circuit parameters rather than in nonlinear recurrent hidden states, offering a practical route to quantum sequence modeling.

By Kuo-Chung Peng, Jiun-Cheng Jiang, Chun-Hua Lin, Yifeng Peng, Junghoon Justin Park, Huan-Hsin Tseng, Hsin-Yi Lin, Kuan-Cheng Chen, Chen-Yu Liu, Shinjae Yoo, Samuel Yen-Chi Chen

benchmarks

arXiv AI

Jun 16

Gated QKAN-FWP: Scalable Quantum-inspired Sequence Learning

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

reinforcement-learning benchmarks

arXiv AI

Jul 23

Hybrid LLM-Guided Search for Quantum Reservoir Architecture Design

arXiv:2607. 19506v1 Announce Type: cross Abstract: Quantum reservoir computing (QRC) uses fixed quantum dynamics as a high-dimensional temporal feature map and trains only a lightweight classical readout.

By Krishna Bhatia, Gautami Sanjay Naik

llms agents benchmarks

arXiv AI

Jul 21

A Quantum-Classical Hybrid Framework for Multivariate Time-Series Forecasting Complexity-Fidelity Trade-offs and Limitations

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

efficiency benchmarks

arXiv Machine Learning

Jul 15

Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning

arXiv:2506. 21324v3 Announce Type: replace-cross Abstract: Neuromorphic and quantum computing have recently emerged as promising paradigms for advancing artificial intelligence, each offering complementary strengths.

By Jiechen Chen, Bipin Rajendran, Osvaldo Simeone

arXiv Machine Learning

Jul 31

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

arXiv:2607. 27945v1 Announce Type: cross Abstract: Sequence models must decide what to write into memory and what to retain.

By Kuo-Chung Peng, Samuel Yen-Chi Chen, Jiun-Cheng Jiang, Chen-Yu Liu, En-Jui Kuo, Yun-Yuan Wang, Tzung-Chi Huang, Prayag Tiwari, Chi-Sheng Chen, Chun-Hua Lin, Yu-Chao Hsu, Tai-Yue Li, Saif Al-Kuwari, Simon See, Kuan-Cheng Chen, Nan-Yow Chen, Hsi-Sheng Goan

benchmarks

arXiv Machine Learning

1d ago

Hybrid quantum recurrent neural network for remaining useful life prediction of turbofan engines

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

benchmarks

arXiv Machine Learning

Jun 24

Quantum Adaptive Self-Attention for Quantum Transformer Models

arXiv:2504. 05336v4 Announce Type: replace-cross Abstract: A recurring weakness in quantum machine learning (QML) is that reported ``quantum advantages'' are seldom tested against a \emph{capacity-matched} classical control, leaving it unclear whether a gain comes from the quantum substrate or from the architectural change that accompanies it.

By Chi-Sheng Chen, En-Jui Kuo

llms benchmarks

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