In other words, the generation of the response is based on generative models in the brain which code auditory information and produce predictions of which sounds are likely to occur in the near future.
Finally, Genovo, an assembler based on generative probabilistic model of read generation, was selected because it uses an iterative algorithm able to estimate the number of genomes in the populations and denoise 454 sequence data [ 22].
The approach is aimed at addressing wind loading and wind impact requirements based on generative parametric modelling and performance analysis that integrates physical parameters at the architectural and urban scales and performance criteria can support filtering and optimization relative to prevailing wind conditions.
In contrast, our methods are based on generative probabilistic models of both RNA-Seq data and isoform frequencies with splice graph edges weighted by parameters representing RNA processing conditional probabilities.
To enhance creativity and productivity, new teaching methods that are experimented on, developed and taught will be closely based on generative and intuitive design tools.
A Bayesian approach based on a generative model requires one to fully specify how the variables of interest are interrelated statistically.
Also, NMF can be statistically interpreted as a parameter estimation based on a generative model of data, and the distribution of the model defines the objective function (divergence) in NMF.
The semi-synthetic dataset was generated by artificially simulated CRM structures with a third-order Markov model for background sequences and planting real TFBSs from the TRANSFAC database (Wingender et al., 2000) into the simulated background sequences based on the generative model for the HMM-based TFBS prediction tool Baycis and published in Lin et al. (2008).
This asymmetry is also consistent with functional architectures implied by theories of perceptual inference in the brain, based on hierarchical generative models.
The aim of this paper is to propose an urban object recognition algorithm for urban robotic missions with useful properties: online processing, classification results with probabilistic outputs, and training with a few examples based on a generative model.
