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Marco Scutari
Bayesian networks (BNs) are a foundational model in machine learning and causal inference. Their graphical structure can handle high-dimensional problems, divide them into a sparse collection of smaller ones, underlies Judea Pearl?s causality, and determ...
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Yan Wang, Lei Zhao, Longhao Qiu, Jinjin Wang and Chenmu Li
The underwater maneuvering platform generates self-noise when sailing, which shows spatial directionality to the arrays fixed on the platform. In this paper, it is called spatially colored noise (SCN). The direction of arrival (DOA) estimation results ar...
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Shuo Chen, Haojie Li, Lanjie Zhang, Mingyu Zhou and Xuehua Li
In the massive machine type of communication (mMTC), grant-free non-orthogonal multiple access (NOMA) is receiving more and more attention because it can skip the complex grant process to allocate non-orthogonal resources to serve more users. To address ...
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Ganeshchandra Mallya, Mohamed M. Hantush and Rao S. Govindaraju
Effective water quality management and reliable environmental modeling depend on the availability, size, and quality of water quality (WQ) data. Observed stream water quality data are usually sparse in both time and space. Reconstruction of water quality...
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Jian Xu, Kean Chen, Lei Wang and Jiangong Zhang
Low-frequency sound field reconstruction in an enclosed space has many applications where the plane wave approximation of acoustic modes plays a crucial role. However, the basis mismatch of the plane wave directions degrades the approximation accuracy. I...
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Guolong Liang, Zhibo Shi, Longhao Qiu, Sibo Sun and Tian Lan
Direction-of-arrival (DOA) estimation in a spatially isotropic white noise background has been widely researched for decades. However, in practice, such as underwater acoustic ambient noise in shallow water, the ambient noise can be spatially colored, wh...
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Ming Li, Ren Zhang and Kefeng Liu
There are two challenges in the comprehensive marine hazard assessment. The influencing mechanism of marine disaster is uncertain and disaster data are sparse. Aiming at the uncertain knowledge and small sample in assessment modeling, we combine the info...
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Taiyong Li, Zhenda Hu, Yanchi Jia, Jiang Wu and Yingrui Zhou
Crude oil is one of the most important types of energy and its prices have a great impact on the global economy. Therefore, forecasting crude oil prices accurately is an essential task for investors, governments, enterprises and even researchers. However...
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