International Journal for Uncertainty Quantification

期刊简介：The International Journal for Uncertainty Quantification disseminates information of permanent interest in the areas of analysis, modeling, design and control of complex systems in the presence of uncertainty. The journal seeks to emphasize methods that cross stochastic analysis, statistical modeling and scientific computing. Systems of interest are governed by differential equations possibly with multiscale features. Topics of particular interest include representation of uncertainty, propagation of uncertainty across scales, resolving the curse of dimensionality, long-time integration for stochastic PDEs, data-driven approaches for constructing stochastic models, validation, verification and uncertainty quantification for predictive computational science, and visualization of uncertainty in high-dimensional spaces. Bayesian computation and machine learning techniques are also of interest for example in the context of stochastic multiscale systems, for model selection/classification, and decision making. Reports addressing the dynamic coupling of modern experiments and modeling approaches towards predictive science are particularly encouraged. Applications of uncertainty quantification in all areas of physical and biological sciences are appropriate.

【译文】国际不确定性量化杂志传播关于分析、建模、设计和控制复杂系统（存在不确定性时）的永久性信息。该杂志寻求强调跨越随机分析、统计建模和科学计算的方法。感兴趣的系统受可能具有多尺度特性的微分方程控制。特别感兴趣的主题包括不确定性的表示、不确定性在尺度间的传播、解决维度诅咒、随机PDEs的长期积分、构建随机模型的数据驱动方法、预测计算科学的验证、验证和不确定性量化，以及高维空间中不确定性的可视化。在随机多尺度系统、模型选择/分类和决策制定的背景下，贝叶斯计算和机器学习技术也很有兴趣。特别鼓励报告现代实验和建模方法在预测科学中的动态耦合。物理和生物科学所有领域的不确定性量化应用都是合适的。