Zobrazeno 1 - 10
of 400
pro vyhledávání: '"Xin, Jack"'
Autor:
Zheng, Yunling, Xu, Zeyi, Xue, Fanghui, Yang, Biao, Lyu, Jiancheng, Zhang, Shuai, Qi, Yingyong, Xin, Jack
We propose and demonstrate an alternating Fourier and image domain filtering approach for feature extraction as an efficient alternative to build a vision backbone without using the computationally intensive attention. The performance among the light
Externí odkaz:
http://arxiv.org/abs/2407.12217
The investigation of tumor invasion and metastasis dynamics is crucial for advancements in cancer biology and treatment. Many mathematical models have been developed to study the invasion of host tissue by tumor cells. In this paper, we develop a nov
Externí odkaz:
http://arxiv.org/abs/2407.05626
Based on transformed $\ell_1$ regularization, transformed total variation (TTV) has robust image recovery that is competitive with other nonconvex total variation (TV) regularizers, such as TV$^p$, $0
Externí odkaz:
http://arxiv.org/abs/2406.00571
This paper aims to investigate the diffusion behavior of particles moving in stochastic flows under a structure-preserving scheme. We compute the effective diffusivity for normal diffusive random flows and establish the power law between spatial and
Externí odkaz:
http://arxiv.org/abs/2405.19003
We establish global well-posedness and convergence of the score-based generative models (SGM) under minimal general assumptions of initial data for score estimation. For the smooth case, we start from a Lipschitz bound of the score function with opti
Externí odkaz:
http://arxiv.org/abs/2405.16104
We study an interacting particle method (IPM) for computing the large deviation rate function of entropy production for diffusion processes, with emphasis on the vanishing-noise limit and high dimensions. The crucial ingredient to obtain the rate fun
Externí odkaz:
http://arxiv.org/abs/2403.19223
Post-training quantization (PTQ) has emerged as a practical approach to compress large neural networks, making them highly efficient for deployment. However, effectively reducing these models to their low-bit counterparts without compromising the ori
Externí odkaz:
http://arxiv.org/abs/2403.07134
Dengue fever is one of the most deadly mosquito-born tropical infectious diseases. Detailed long range forecast model is vital in controlling the spread of disease and making mitigation efforts. In this study, we examine methods used to forecast deng
Externí odkaz:
http://arxiv.org/abs/2403.07027
G-equations are popular level set Hamilton-Jacobi nonlinear partial differential equations (PDEs) of first or second order arising in turbulent combustion. Characterizing the effective burning velocity (also known as the turbulent burning velocity) i
Externí odkaz:
http://arxiv.org/abs/2401.14575
We introduce an efficient stochastic interacting particle-field (SIPF) algorithm with no history dependence for computing aggregation patterns and near singular solutions of parabolic-parabolic Keller-Segel (KS) chemotaxis system in three space dimen
Externí odkaz:
http://arxiv.org/abs/2309.13554