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To aid assessments of climate change impacts on water related activities in the case study regions (CSRs) of the EC funded project SWURVE, estimates of uncertainty in climate model data need to be developed. In this paper, two methods to estimate uncertain ...
Molecular noise, which arises from the randomness of the discrete events in the cell, significantly influences fundamental biological processes. Discrete-state continuous-time stochastic models (CTMC) can be used to describe such effects, but the calculati ...
[1] The long-term morphological evolution of tidal landforms in response to physical and ecological forcings is a subject of great theoretical and practical importance. Toward the goal of a comprehensive theoretical framework suitable for large-scale, long ...
We consider backward stochastic differential equations (BSDEs) with a particular quadratic generator and study the behaviour of their solu- tions when the probability measure is changed, the filtration is shrunk, or the underlying probability space is transf ...
A method is presented to construct object-related structure observables, such as size, mass, shape, and trajectories from two-dimensional plasma imaging data. The probability distributions of these observables, deduced from measurements of many realization ...
In this paper, the design of probabilistic observers for mass-balance based bioprocess models is investigated. It is assumed that the probability density of every uncertain parameter, input and/or initial state is known a priori. Then, the probability dens ...
We present a new result characterized by an exact integral expression for the approximation error between a probability density and an integer shift invariant estimate obtained from its samples. Unlike the Parzen window estimate, this estimate avoids recom ...
A theoretical model describing the attachment and cytoskeletal coupling of microspheres to the dorsal surface of motile cells was developed. Integral membrane receptors beneath a ligand-coated microsphere are allowed to be either free, attached to the micr ...
We present a general method for maintaining estimates of the distribution of parameters in arbitrary models. This is then applied to the estimation of probability distributions over actions in value-based reinforcement learning. While this approach is simi ...
In this paper the approximating capabilities of fuzzy systems with overlapping Gaussian concepts are considered. The target function is assumed to be sampled either on a regular gird or according to a uniform probability density. By exploiting a connection ...