Probability Theory & Related FieldsA change of variables formula for Stratonovich integrals and existence of solutions for two-point stochastic boundary value problems, Prob. Th. Rel Fields 84 - Dembo, Zeitouni
瞬时换元公式[1](Instantaneous Change of Variable,ICV) 是连续时间normalizing flow (CNF)中一个核心定理。最早由NeurIPS-2018 的best paper 之一的工作 Neural ODE提出。该定理给出了在一个常微分方程定义的变换下,概率密度的变换公式。该定理可以描述为: Theorem(Instantaneous Change of Variables)(Theorem 1 [1...
If the data is incomplete, has missing data points, or has unnoticed (hidden) latent variables, the EM algorithm is a way to find maximum likelihood estimates for model parameters. It is an iterative method of approximating the equation of maximum probability. EM detection is a classification-ba...
How do I find the rate of change? Substitute two points into the average rate of change formula, and simplify it. It does not matter which point is considered the first or second point. Just make sure to stay consistent when substituting into the variables. How do you find the initial va...
We note, however, that while the GWL framing is a natural fit for variables for which (at least on a century timescale) climatological changes with warming are largely time independent, for sea-level change the effects of different GWLs cannot be examined in a time-independent manner, as ...
and the measurement of the multiple variables at stake (knowledge phase), to define measures able to influence such variables (decision phase) and to implement these measures (action phase), taking into account the unpredictable changes of the initial conditions, which would occur during the time....
definition of variables energy poverty okushima assesses energy poverty through a direct measure of energy service use, exploring the regional characteristics of energy or fuel poverty in japan through a new methodology. the measure is a calorific relative poverty measure with multiple thresholds ...
In this article, we analyse the role that artificial intelligence (AI) could play, and is playing, to combat global climate change. We identify two crucial
Fig. 4: Overview of workflow implemented in the present study to integrate mechanistic dispersal kernels and correlative climatic suitability models in simulations of future wind-dispersed species distributions under climate change. Species distribution data (left) are combined with climatic variables to pr...
To make the variables measured at different scales and units comparable for spatial analysis, we used the min-max normalization method (formula: x’ = (x − min) / (max − min), where x’ is the rescaled value, x is the original value, max is the maximum value ...