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pro vyhledávání: '"Yang, Gengzhi"'
As industrial models and designs grow increasingly complex, the demand for optimal control of large-scale dynamical systems has significantly increased. However, traditional methods for optimal control incur significant overhead as problem dimensions
Externí odkaz:
http://arxiv.org/abs/2411.01391
We establish improved complexity estimates of quantum algorithms for linear dissipative ordinary differential equations (ODEs) and show that the time dependence can be fast-forwarded to be sub-linear. Specifically, we show that a quantum algorithm ba
Externí odkaz:
http://arxiv.org/abs/2410.13189
Autor:
Yang, Gengzhi, Li, Yingzhou
Both classical Fourier transform-based methods and neural network methods are widely used in image processing tasks. The former has better interpretability, whereas the latter often achieves better performance in practice. This paper introduces Butte
Externí odkaz:
http://arxiv.org/abs/2211.16578