MULTIFIDELITY ESTIMATORS FOR CORONARY CIRCULATION MODELS UNDER CLINICALLY INFORMED DATA UNCERTAINTY [0.03%]
临床数据不确定性下的冠状循环模型的多保真度估计器
Jongmin Seo,Casey Fleeter,Andrew M Kahn et al.
Jongmin Seo et al.
Numerical models are increasingly used for noninvasive diagnosis and treatment planning in coronary artery disease, where service-based technologies have proven successful in identifying hemodynamically significant and hence potentially dan...
BAYESIAN INFERENCE OF STOCHASTIC REACTION NETWORKS USING MULTIFIDELITY SEQUENTIAL TEMPERED MARKOV CHAIN MONTE CARLO [0.03%]
基于多保真序贯 tempered markov chain monte carlo 的 stochastic reaction networks 的 bayesian 推断
Thomas A Catanach,Huy D Vo,Brian Munsky
Thomas A Catanach
Stochastic reaction network models are often used to explain and predict the dynamics of gene regulation in single cells. These models usually involve several parameters, such as the kinetic rates of chemical reactions, that are not directl...
INTERACTIVE VISUALIZATION OF PROBABILITY AND CUMULATIVE DENSITY FUNCTIONS [0.03%]
概率和累积密度函数的交互式可视化方法
Kristin Potter,Robert M Kirby,Dongbin Xiu et al.
Kristin Potter et al.
The probability density function (PDF), and its corresponding cumulative density function (CDF), provide direct statistical insight into the characterization of a random process or field. Typically displayed as a histogram, one can infer pr...