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NIPS
1997
15 years 8 months ago
Learning Generative Models with the Up-Propagation Algorithm
Up-propagation is an algorithm for inverting and learning neural network generative models. Sensory input is processed by inverting a model that generates patterns from hidden var...
Jong-Hoon Oh, H. Sebastian Seung
BMCBI
2010
176views more  BMCBI 2010»
15 years 7 months ago
Bayesian statistical modelling of human protein interaction network incorporating protein disorder information
Background: We present a statistical method of analysis of biological networks based on the exponential random graph model, namely p2-model, as opposed to previous descriptive app...
Svetlana Bulashevska, Alla Bulashevska, Roland Eil...
BMCBI
2007
139views more  BMCBI 2007»
15 years 7 months ago
Improving model predictions for RNA interference activities that use support vector machine regression by combining and filterin
Background: RNA interference (RNAi) is a naturally occurring phenomenon that results in the suppression of a target RNA sequence utilizing a variety of possible methods and pathwa...
Andrew S. Peek
BC
2005
127views more  BC 2005»
15 years 7 months ago
Computational modeling and exploration of contour integration for visual saliency
Abstract Weproposeacomputationalmodelofcontourintegration for visual saliency. The model uses biologically plausible devices to simulate how the representations of elements aligned...
T. Nathan Mundhenk, Laurent Itti
JCNS
2000
86views more  JCNS 2000»
15 years 6 months ago
Computational Modeling of Orientation Tuning Dynamics in Monkey Primary Visual Cortex
In the primate visual pathway, orientation tuning of neurons is first observed in the primary visual cortex. The LGN cells that comprise the thalamic input to V1 are not orientati...
M. C. Pugh, Dario L. Ringach, Robert Shapley, M. J...