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» Probabilistic Neural Network Models for Sequential Data
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KDD
2004
ACM
170views Data Mining» more  KDD 2004»
14 years 1 months ago
Estimating the size of the telephone universe: a Bayesian Mark-recapture approach
Mark-recapture models have for many years been used to estimate the unknown sizes of animal and bird populations. In this article we adapt a finite mixture mark-recapture model i...
David Poole
NN
2007
Springer
14 years 2 months ago
Impact of Higher-Order Correlations on Coincidence Distributions of Massively Parallel Data
The signature of neuronal assemblies is the higher-order correlation structure of the spiking activity of the participating neurons. Due to the rapid progress in recording technol...
Sonja Grün, Moshe Abeles, Markus Diesmann
BMCBI
2008
107views more  BMCBI 2008»
13 years 8 months ago
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Background: A better understanding of the mechanisms involved in gas-phase fragmentation of peptides is essential for the development of more reliable algorithms for high-throughp...
Cong Zhou, Lucas D. Bowler, Jianfeng Feng
NIPS
2004
13 years 9 months ago
Bayesian inference in spiking neurons
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
Sophie Deneve
ICANN
2009
Springer
14 years 2 months ago
Using Kernel Basis with Relevance Vector Machine for Feature Selection
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...
Frederic Suard, David Mercier