Zobrazeno 1 - 10
of 11 581
pro vyhledávání: '"CHEN, NAN"'
State estimation in multi-layer turbulent flow fields with only a single layer of partial observation remains a challenging yet practically important task. Applications include inferring the state of the deep ocean by exploiting surface observations.
Externí odkaz:
http://arxiv.org/abs/2412.11042
We present the Quantum Kernel-Based Long short-memory (QK-LSTM) network, which integrates quantum kernel methods into classical LSTM architectures to enhance predictive accuracy and computational efficiency in climate time-series forecasting tasks, s
Externí odkaz:
http://arxiv.org/abs/2412.08851
In this study, we propose a novel architecture, the Quantum Pointwise Convolution, which incorporates pointwise convolution within a quantum neural network framework. Our approach leverages the strengths of pointwise convolution to efficiently integr
Externí odkaz:
http://arxiv.org/abs/2412.01241
Data assimilation (DA) combines partial observations with a dynamical model to improve state estimation. Filter-based DA uses only past and present data and is the prerequisite for real-time forecasts. Smoother-based DA exploits both past and future
Externí odkaz:
http://arxiv.org/abs/2411.05870
Understanding the interactions between the El Nino-Southern Oscillation (ENSO) and the Madden-Julian Oscillation (MJO) is essential to studying climate variabilities and predicting extreme weather events. Here, we develop a stochastic conceptual mode
Externí odkaz:
http://arxiv.org/abs/2411.05264
Autor:
Andreou, Marios, Chen, Nan
The Conditional Gaussian Nonlinear System (CGNS) is a broad class of nonlinear stochastic dynamical systems. Given the trajectories for a subset of state variables, the remaining follow a Gaussian distribution. Despite the conditionally linear struct
Externí odkaz:
http://arxiv.org/abs/2410.24056
Sea ice plays a crucial role in the climate system, particularly in the Marginal Ice Zone (MIZ), a transitional area consisting of fragmented ice between the open ocean and consolidated pack ice. As the MIZ expands, understanding its dynamics becomes
Externí odkaz:
http://arxiv.org/abs/2410.23138
Deep learning is widely used to predict complex dynamical systems in many scientific and engineering areas. However, the black-box nature of these deep learning models presents significant challenges for carrying out simultaneous data assimilation (D
Externí odkaz:
http://arxiv.org/abs/2410.20072
Autor:
Wang, Zilong, Chen, Nan, Qiu, Luna K., Yue, Ling, Guo, Geli, Ou, Yang, Jiang, Shiqi, Yang, Yuqing, Qiu, Lili
In recent years, the rapid aging of the global population has led to an increase in cognitive disorders, such as Alzheimer's disease, presenting significant public health challenges. Although no effective treatments currently exist to reverse Alzheim
Externí odkaz:
http://arxiv.org/abs/2410.19733
Subject-driven text-to-image (T2I) customization has drawn significant interest in academia and industry. This task enables pre-trained models to generate novel images based on unique subjects. Existing studies adopt a self-reconstructive perspective
Externí odkaz:
http://arxiv.org/abs/2409.05606