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Background: Identifying large gene regulatory networks is an important task, while the acquisition of data through perturbation experiments (e.g., gene switches, RNAi, heterozygotes) is expensive. It is thus desirable to use an identification ...
In this paper we address an observational validation of recent theoretical results on the structure of the probability density function (pdf) of daily streamflows through the analysis of data pertaining to several catchments covering various sizes, climati ...
With the rapid expansion in the use of computers for producing digitalized textual documents, the need of automatic systems for organizing and retrieving the information contained in large databases has become essential. In general, information retrieval s ...
The very existence of urban formations on all inhabited continents and throughout the history of mankind since the 3rd millennium B.C. leads to suppose a tendency of some structured societies to maximize interaction by minimizing physical distance. Were th ...
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 ...
With the rapid expansion in the use of computers for producing digitalized textual documents, the need of automatic systems for organizing and retrieving the information contained in large databases has become essential. In general, information retrieval s ...
Distribution of the monocarboxylate transporter MCT1 has been investigated in the cortex of normal adult human brain. Similarly to the glucose transporter GLUT1 55 kDa isoform, MCT1 was found to be strongly expressed on blood vessels in all cortical layers ...
This paper addresses the issue of segmentation and recognition of text embedded in video sequences from their associated text image sequence extracted by a text detection module. To this end, we propose a probabilistic algorithm based on Bayesian adaptive ...
We describe a novel variational segmentation algorithm designed to split an image in two regions based on their intensity distributions. A functional is proposed to integrate the probability density functions of both regions within the optimization process ...
The paper presents an alternative approach to automatic recognition of speech in which each targeted word is classified by a separate binary classifier against all other sounds. No time alignment is done. To build a recognizer for N words, N parallel binar ...