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pro vyhledávání: '"Yule A"'
Understanding the neural basis of behavior is a fundamental goal in neuroscience. Current research in large-scale neuro-behavioral data analysis often relies on decoding models, which quantify behavioral information in neural data but lack details on
Externí odkaz:
http://arxiv.org/abs/2410.09614
Autor:
Gao, Mingyuan, Sheng, Chong, Zhao, Yule, He, Runqiu, Lu, Liangliang, Chen, Wei, Ding, Kun, Zhu, Shining, Liu, Hui
Publikováno v:
Physical Review B 110, 094308 (2024)
Entanglement entropy characterizes the correlation of multi-particles and unveils the crucial features of open quantum systems. However, the experimental realization of exploring entanglement in non-Hermitian systems remains a challenge. In parallel,
Externí odkaz:
http://arxiv.org/abs/2409.10130
Pansharpening is a challenging image fusion task that involves restoring images using two different modalities: low-resolution multispectral images (LRMS) and high-resolution panchromatic (PAN). Many end-to-end specialized models based on deep learni
Externí odkaz:
http://arxiv.org/abs/2409.06980
Large Language Models (LLMs) have performed exceptionally in various text-generative tasks, including question answering, translation, code completion, etc. However, the over-assistance of LLMs has raised the challenge of "jailbreaking", which induce
Externí odkaz:
http://arxiv.org/abs/2407.04295
Medical image classification plays a crucial role in computer-aided clinical diagnosis. While deep learning techniques have significantly enhanced efficiency and reduced costs, the privacy-sensitive nature of medical imaging data complicates centrali
Externí odkaz:
http://arxiv.org/abs/2407.02261
Gaussian Processes (GPs) and Linear Dynamical Systems (LDSs) are essential time series and dynamic system modeling tools. GPs can handle complex, nonlinear dynamics but are computationally demanding, while LDSs offer efficient computation but lack th
Externí odkaz:
http://arxiv.org/abs/2407.00397
Autor:
Chen, Guanzhou, Zhang, Kaiqi, Zhang, Xiaodong, Xie, Hong, Yang, Haobo, Tan, Xiaoliang, Wang, Tong, Ma, Yule, Wang, Qing, Cao, Jinzhou, Cui, Weihong
The Light Use Efficiency model, epitomized by the CASA model, is extensively applied in the quantitative estimation of vegetation Net Primary Productivity. However, the classic CASA model is marked by significant complexity: the estimation of environ
Externí odkaz:
http://arxiv.org/abs/2406.19969
Deep neural networks for image super-resolution (ISR) have shown significant advantages over traditional approaches like the interpolation. However, they are often criticized as 'black boxes' compared to traditional approaches with solid mathematical
Externí odkaz:
http://arxiv.org/abs/2405.07919
Currently, machine learning-based methods for remote sensing pansharpening have progressed rapidly. However, existing pansharpening methods often do not fully exploit differentiating regional information in non-local spaces, thereby limiting the effe
Externí odkaz:
http://arxiv.org/abs/2404.07543
Graph neural networks (GNN) have achieved remarkable success in a wide range of tasks by encoding features combined with topology to create effective representations. However, the fundamental problem of understanding and analyzing how graph topology
Externí odkaz:
http://arxiv.org/abs/2404.07493