Retrieving past quantum features with deep hybrid classical-quantum reservoir computing
Machine learning techniques have achieved impressive results in recent years and the
possibility of harnessing the power of quantum physics opens new promising avenues to …
possibility of harnessing the power of quantum physics opens new promising avenues to …
Feedback-driven quantum reservoir computing for time-series analysis
K Kobayashi, K Fujii, N Yamamoto - arXiv preprint arXiv:2406.15783, 2024 - arxiv.org
Quantum reservoir computing (QRC) is a highly promising computational paradigm that
leverages quantum systems as a computational resource for nonlinear information …
leverages quantum systems as a computational resource for nonlinear information …
Prediction of chaotic dynamics and extreme events: A recurrence-free quantum reservoir computing approach
In chaotic dynamical systems, extreme events manifest in time series as unpredictable large-
amplitude peaks. Although deterministic, extreme events appear seemingly randomly, which …
amplitude peaks. Although deterministic, extreme events appear seemingly randomly, which …
Learning Interpretable Dynamical Systems Models from Multimodal Empirical Time Series
MB Brenner - 2024 - archiv.ub.uni-heidelberg.de
Dynamical systems (DS) theory provides a rich framework to model dynamic processes
across science and engineering. However, traditional scientific model building is often …
across science and engineering. However, traditional scientific model building is often …
[引用][C] Put forward by Manuel Benjamin Brenner born in: Bietigheim-Bissingen Oral examination: 03.07. 2024
MB Brenner