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» Using Neural Nets to Estimate Evolutionary Parameters
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IJCNN
2007
IEEE
14 years 2 months ago
Probability Density Function Estimation Using Orthogonal Forward Regression
— Using the classical Parzen window estimate as the target function, the kernel density estimation is formulated as a regression problem and the orthogonal forward regression tec...
Sheng Chen, Xia Hong, Chris J. Harris
NIPS
2007
13 years 9 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
BC
2006
63views more  BC 2006»
13 years 8 months ago
A Quantitative Theory of Neural Computation
We show how a general quantitative theory of neural computation can be used to explain two recent experimental findings in neuroscience. The first of these findings is that in hum...
Leslie G. Valiant
CEC
2005
IEEE
13 years 10 months ago
Making soccer kicks better: a study in particle swarm optimization and evolution strategies
Biomechanics is a science of examining the internal and external forces on the human body. In biomechanics, forward dynamics simulation models can be used to study optimal control ...
Namrata Khemka, Christian Jacob, Gerald Cole
BMCBI
2010
185views more  BMCBI 2010»
13 years 8 months ago
ABCtoolbox: a versatile toolkit for approximate Bayesian computations
Background: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractab...
Daniel Wegmann, Christoph Leuenberger, Samuel Neue...