Zobrazeno 1 - 10
of 4 709
pro vyhledávání: '"Engquist A"'
We propose and analyze a class of adaptive sampling algorithms for multimodal distributions on a bounded domain, which share a structural resemblance to the classic overdamped Langevin dynamics. We first demonstrate that this class of linear dynamics
Externí odkaz:
http://arxiv.org/abs/2411.15220
Numerical homogenization of multiscale equations typically requires taking an average of the solution to a microscale problem. Both the boundary conditions and domain size of the microscale problem play an important role in the accuracy of the homoge
Externí odkaz:
http://arxiv.org/abs/2308.07563
Autor:
Michael C. Robertson, Maria Chang Swartz, Karen M. Basen-Engquist, Yisheng Li, Kristofer Jennings, Debbe Thompson, Tom Baranowski, Elena Volpi, Elizabeth J. Lyons
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-15 (2024)
Abstract Background Older adult women often do not engage in sufficient physical activity (PA) and can encounter biological changes that exacerbate the negative effects of inadequate activity. Wearable activity monitors can facilitate PA initiation,
Externí odkaz:
https://doaj.org/article/e69da11084694703b2b5e0cb7e461d03
This paper develops and analyzes a stochastic derivative-free optimization strategy. A key feature is the state-dependent adaptive variance. We prove global convergence in probability with algebraic rate and give the quantitative results in numerical
Externí odkaz:
http://arxiv.org/abs/2302.04370
A large class of inverse problems for PDEs are only well-defined as mappings from operators to functions. Existing operator learning frameworks map functions to functions and need to be modified to learn inverse maps from data. We propose a novel arc
Externí odkaz:
http://arxiv.org/abs/2301.11167
Autor:
Preena Loomba, Margaret R. Raber, Mayra Aquino, Nikki Rincon, Lori Rumfield, Karen M. Basen‐Engquist, Ruth Rechis
Publikováno v:
Cancer Medicine, Vol 13, Iss 16, Pp n/a-n/a (2024)
Abstract Background Food insecurity, an economic and social condition of limited food access, is associated with poor diet quality—a risk factor for several common cancers. The University of Texas MD Anderson Cancer Center supports healthy food acc
Externí odkaz:
https://doaj.org/article/4b7ba6d2f110468da56b8788a8b37914
We propose a new gradient descent algorithm with added stochastic terms for finding the global optimizers of nonconvex optimization problems. A key component in the algorithm is the adaptive tuning of the randomness based on the value of the objectiv
Externí odkaz:
http://arxiv.org/abs/2204.05923
Autor:
Katherine Oestman, Ruth Rechis, Pamela A. Williams, Jill A. Brown, Katherine Treiman, Brittany Zulkiewicz, Michael T. Walsh, Karen Basen-Engquist, Trina Rodriguez, Catherine Chennisi, Amber Macneish, Alise Neff, Mike Pomeroy, Faiyaz A. Bhojani, Ernest Hawk
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-12 (2024)
Abstract Background Community initiatives can shape health behaviors, such as physical activity and dietary habits, across a population and help reduce the risk of developing chronic disease. To achieve this goal and impact health outcomes, Pasadena
Externí odkaz:
https://doaj.org/article/3661d5216b4e4f6eba5df1b8f606e57e
The generalization capacity of various machine learning models exhibits different phenomena in the under- and over-parameterized regimes. In this paper, we focus on regression models such as feature regression and kernel regression and analyze a gene
Externí odkaz:
http://arxiv.org/abs/2201.09223
Autor:
Elise N. Engquist, Anna Greco, Leo A.B. Joosten, Baziel G.M. van Engelen, Christopher R.S. Banerji, Peter S. Zammit
Publikováno v:
iScience, Vol 27, Iss 6, Pp 109947- (2024)
Summary: The routine need for myonuclear turnover in skeletal muscle, together with more sporadic demands for hypertrophy and repair, are performed by resident muscle stem cells called satellite cells. Muscular dystrophies are characterized by muscle
Externí odkaz:
https://doaj.org/article/41dea0aec9644f16875e162cd583eb18