Zobrazeno 1 - 10
of 2 550
pro vyhledávání: '"LU Jianfeng"'
Autor:
Muhammad Safeer Abbas, Muhammad Afzaal, Farhan Saeed, Aasma Asghar, Lu Jianfeng, Aftab Ahmad, Qudrat Ullah, Samreen Elahi, Huda Ateeq, Yasir Abbas Shah, Muhammad Nouman, Mohd Asif Shah
Publikováno v:
International Journal of Food Properties, Vol 26, Iss 1, Pp 1324-1350 (2023)
ABSTRACTThe demand for probiotic-based functional food is increasing globally owing to its health-endorsing attributes. There are various driving forces behind probiotic therapy. However, Intestinal dysbiosis in humans is the prime driving force behi
Externí odkaz:
https://doaj.org/article/3b73ec00b00d4c8aad55f26ef001ca4c
Publikováno v:
Applied Mathematics and Nonlinear Sciences, Vol 9, Iss 1 (2024)
Because of the existing problems in the business management mode of enterprises, this paper analyzes the reasons for their existence and proposes corresponding safeguard measures to optimize the business management mode. Firstly, the evaluation model
Externí odkaz:
https://doaj.org/article/a4cc027b370b4e379d3ed973466e8db1
Publikováno v:
Journal of Isotopes, Vol 35, Iss 4, Pp 304-310 (2022)
NaI spectrometer is commonly used in nuclear emergency monitoring to realize dose rate monitoring and γ radionuclide identification. This paper introduces the calibration of the direct conversion of energy spectrum to dose for a 3″×3″ NaI spect
Externí odkaz:
https://doaj.org/article/42b279b6be18492cb55f5a3ffeb31f48
Due to the sensitivity of data, Federated Learning (FL) is employed to enable distributed machine learning while safeguarding data privacy and accommodating the requirements of various devices. However, in the context of semi-decentralized FL, client
Externí odkaz:
http://arxiv.org/abs/2412.11448
Autor:
Rohatgi, Dhruv, Marwah, Tanya, Lipton, Zachary Chase, Lu, Jianfeng, Moitra, Ankur, Risteski, Andrej
Graph neural networks (GNNs) are the dominant approach to solving machine learning problems defined over graphs. Despite much theoretical and empirical work in recent years, our understanding of finer-grained aspects of architectural design for GNNs
Externí odkaz:
http://arxiv.org/abs/2410.09867
Posterior sampling in high-dimensional spaces using generative models holds significant promise for various applications, including but not limited to inverse problems and guided generation tasks. Despite many recent developments, generating diverse
Externí odkaz:
http://arxiv.org/abs/2410.02078
The use of guidance in diffusion models was originally motivated by the premise that the guidance-modified score is that of the data distribution tilted by a conditional likelihood raised to some power. In this work we clarify this misconception by r
Externí odkaz:
http://arxiv.org/abs/2409.13074
Autor:
Lu, Jianfeng, Wang, Yuliang
The particle filter (PF), also known as the sequential Monte Carlo (SMC), is designed to approximate high-dimensional probability distributions and their normalizing constants in the discrete-time setting. To reduce the variance of the Monte Carlo ap
Externí odkaz:
http://arxiv.org/abs/2409.02399
Autor:
Liu, Kaizhao, Lu, Jianfeng
We investigate the dependence of physical observable of open quantum systems with Bosonic bath on the bath correlation function. We provide an error estimate of the difference of physical observable induced by the variation of bath correlation functi
Externí odkaz:
http://arxiv.org/abs/2408.04009
We study a qDRIFT-type randomized method to simulate Lindblad dynamics by decomposing its generator into an ensemble of Lindbladians, $\mathcal{L} = \sum_{a \in \mathcal{A}} \mathcal{L}_a$, where each $\mathcal{L}_a$ involves only a single jump opera
Externí odkaz:
http://arxiv.org/abs/2407.06594