Zobrazeno 1 - 10
of 13 728
pro vyhledávání: '"XIE, Wei"'
Driven by the critical challenges in biomanufacturing, including high complexity and high uncertainty, we propose a comprehensive and computationally efficient sensitivity analysis framework for general nonlinear policy-augmented knowledge graphical
Externí odkaz:
http://arxiv.org/abs/2411.13396
Autor:
Xie, Wei
An approach to supervised learning in spiking neural networks is presented using a gradient-free method combined with spike-timing-dependent plasticity for image recognition. The proposed network architecture is scalable to multiple layers, enabling
Externí odkaz:
http://arxiv.org/abs/2410.16524
Do Large Language Models Truly Grasp Mathematics? An Empirical Exploration From Cognitive Psychology
Autor:
Xie, Wei, Ma, Shuoyoucheng, Wang, Zhenhua, Wang, Enze, Chen, Kai, Sun, Xiaobing, Wang, Baosheng
The cognitive mechanism by which Large Language Models (LLMs) solve mathematical problems remains a widely debated and unresolved issue. Currently, there is little interpretable experimental evidence that connects LLMs' problem-solving with human cog
Externí odkaz:
http://arxiv.org/abs/2410.14979
Autor:
Fu, Shao-Yu, Xu, Dong, Lei, Wei-Hua, Postigo, Antonio de Ugarte, Kann, D. Alexander, Thöne, Christina C., Fernández, José Feliciano Agüí, Shuang-Xi, Yi, Xie, Wei, Zou, Yuan-Chuan, Liu, Xing, Jiang, Shuai-Qing, Lu, Tian-Hua, An, Jie, Zhu, Zi-Pei, Zheng, Jie, Tang, Qing-Wen, Zhao, Peng-Wei, Xin, Li-Ping, Wei, Jian-Yan
We present our optical observations and multi-wavelength analysis of the GRB\,200613A detected by \texttt{Fermi} satellite. Time-resolved spectral analysis of the prompt $\gamma$-ray emission was conducted utilizing the Bayesian block method to deter
Externí odkaz:
http://arxiv.org/abs/2407.15824
Autor:
Yin, Yi-Han Iris, Zhang, Bin-Bin, Yang, Jun, Sun, Hui, Zhang, Chen, Shao, Yi-Xuan, Hu, You-Dong, Zhu, Zi-Pei, Xu, Dong, An, Li, Gao, He, Wu, Xue-Feng, Zhang, Bing, Castro-Tirado, Alberto Javier, Pandey, Shashi B., Rau, Arne, Lei, Weihua, Xie, Wei, Ghirlanda, Giancarlo, Piro, Luigi, O'Brien, Paul, Troja, Eleonora, Jonker, Peter, Yu, Yun-Wei, An, Jie, Chen, Run-Chao, Chen, Yi-Jing, Dong, Xiao-Fei, Eyles-Ferris, Rob, Fan, Zhou, Fu, Shao-Yu, Fynbo, Johan P. U., Gao, Xing, Huang, Yong-Feng, Jiang, Shuai-Qing, Jiang, Ya-Hui, Julakanti, Yashaswi, Kuulkers, Erik, Lao, Qing-Hui, Li, Dongyue, Ling, Zhi-Xing, Liu, Xing, Liu, Yuan, Mou, Jia-Yu, Pan, Xin, Varun, Wei, Daming, Wu, Qinyu, Yadav, Muskan, Yang, Yu-Han, Yuan, Weimin, Zhang, Shuang-Nan
Publikováno v:
2024, ApJL, 975, L27
The Einstein Probe (EP) achieved its first detection and localization of a bright X-ray flare, EP240219a, on 2024 February 19, during its commissioning phase. Subsequent targeted searches triggered by the EP240219a alert identified a faint, untrigger
Externí odkaz:
http://arxiv.org/abs/2407.10156
Autor:
Choy, Keilung, Xie, Wei
Motivated by the pressing challenges in the digital twin development for biomanufacturing systems, we introduce an adjoint sensitivity analysis (SA) approach to expedite the learning of mechanistic model parameters. In this paper, we consider enzymat
Externí odkaz:
http://arxiv.org/abs/2405.04011
Biomanufacturing innovation relies on an efficient Design of Experiments (DoEs) to optimize processes and product quality. Traditional DoE methods, ignoring the underlying bioprocessing mechanisms, often suffer from a lack of interpretability and sam
Externí odkaz:
http://arxiv.org/abs/2405.03913
To support mechanism online learning and facilitate digital twin development for biomanufacturing processes, this paper develops an efficient Bayesian inference approach for partially observed enzymatic stochastic reaction network (SRN), a fundamenta
Externí odkaz:
http://arxiv.org/abs/2405.02783
In this paper, we develop a general framework for multicontinuum homogenization in perforated domains. The simulations of problems in perforated domains are expensive and, in many applications, coarse-grid macroscopic models are developed. Many previ
Externí odkaz:
http://arxiv.org/abs/2404.17471
In this paper, we propose a novel multiscale model reduction strategy tailored to address the Poisson equation within heterogeneous perforated domains. The numerical simulation of this intricate problem is impeded by its multiscale characteristics, n
Externí odkaz:
http://arxiv.org/abs/2404.17372