Zobrazeno 1 - 10
of 2 097
pro vyhledávání: '"Li,Weiming"'
An asymptotic-preserving (AP) implicit-explicit PN numerical scheme is proposed for the gray model of the radiative transfer equation, where the first- and second-order numerical schemes are discussed for both the linear and nonlinear models. The AP
Externí odkaz:
http://arxiv.org/abs/2410.23650
Sample covariance matrices from multi-population typically exhibit several large spiked eigenvalues, which stem from differences between population means and are crucial for inference on the underlying data structure. This paper investigates the asym
Externí odkaz:
http://arxiv.org/abs/2409.08715
Autor:
Ma, Jianjun, Song, Yuheng, Zhang, Mingxia, Liu, Guohao, Li, Weiming, Federici, John F., Mittleman, Daniel M.
With the growing demand for higher wireless data rates, the interest in extending the carrier frequency of wireless links to the terahertz (THz) range has significantly increased. For long-distance outdoor wireless communications, THz channels may su
Externí odkaz:
http://arxiv.org/abs/2409.00114
Large language models (LLMs) demonstrate extraordinary abilities in a wide range of natural language processing (NLP) tasks. In this paper, we show that, beyond text understanding capability, LLMs are capable of processing text layouts that are denot
Externí odkaz:
http://arxiv.org/abs/2407.05750
Autor:
Hao, Xiaoshuai, Wei, Mengchuan, Yang, Yifan, Zhao, Haimei, Zhang, Hui, Zhou, Yi, Wang, Qiang, Li, Weiming, Kong, Lingdong, Zhang, Jing
Driving systems often rely on high-definition (HD) maps for precise environmental information, which is crucial for planning and navigation. While current HD map constructors perform well under ideal conditions, their resilience to real-world challen
Externí odkaz:
http://arxiv.org/abs/2406.12214
Autor:
Zhang, Chengyang, Li, Weiming, Li, Gang, Song, Huina, Song, Zhaohui, Wang, Xueqian, Plaza, Antonio
Detection of changes in heterogeneous remote sensing images is vital, especially in response to emergencies like earthquakes and floods. Current homogenous transformation-based change detection (CD) methods often suffer from high computation and memo
Externí odkaz:
http://arxiv.org/abs/2405.01920
Point scene understanding is a challenging task to process real-world scene point cloud, which aims at segmenting each object, estimating its pose, and reconstructing its mesh simultaneously. Recent state-of-the-art method first segments each object
Externí odkaz:
http://arxiv.org/abs/2403.16431
Adversarial inverse reinforcement learning (AIRL) stands as a cornerstone approach in imitation learning, yet it faces criticisms from prior studies. In this paper, we rethink AIRL and respond to these criticisms. Criticism 1 lies in Inadequate Polic
Externí odkaz:
http://arxiv.org/abs/2403.14593
Depth-based 3D hand pose estimation is an important but challenging research task in human-machine interaction community. Recently, dense regression methods have attracted increasing attention in 3D hand pose estimation task, which provide a low comp
Externí odkaz:
http://arxiv.org/abs/2403.13405
We present an asymptotic-preserving (AP) numerical method for solving the three-temperature radiative transfer model, which holds significant importance in inertial confinement fusion. A carefully designedsplitting method is developed that can provid
Externí odkaz:
http://arxiv.org/abs/2402.19191