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NIPS
2008
15 years 7 months ago
Evaluating probabilities under high-dimensional latent variable models
We present a simple new Monte Carlo algorithm for evaluating probabilities of observations in complex latent variable models, such as Deep Belief Networks. While the method is bas...
Iain Murray, Ruslan Salakhutdinov
ICANN
2010
Springer
15 years 7 months ago
A Bilinear Model for Consistent Topographic Representations
Visual recognition faces the difficult problem of recognizing objects despite the multitude of their appearances. Ample neuroscientific evidence shows that the cortex uses a topogr...
Urs Bergmann, Christoph von der Malsburg
IJPRAI
2000
83views more  IJPRAI 2000»
15 years 5 months ago
Practical Issues in Modeling Large Diagnostic Systems with Multiply Sectioned Bayesian Networks
As Bayesian networks become widely accepted as a normative formalism for diagnosis based on probabilistic knowledge, they are applied to increasingly larger problem domains. These...
Yanping Xiang, Kristian G. Olesen, Finn Verner Jen...
AROBOTS
1999
104views more  AROBOTS 1999»
15 years 5 months ago
Reinforcement Learning Soccer Teams with Incomplete World Models
We use reinforcement learning (RL) to compute strategies for multiagent soccer teams. RL may pro t signi cantly from world models (WMs) estimating state transition probabilities an...
Marco Wiering, Rafal Salustowicz, Jürgen Schm...
IEEEARES
2006
IEEE
16 years 2 days ago
Bayesian Networks Implementation of the Dempster Shafer Theory to Model Reliability Uncertainty
In many reliability studies based on data, reliability engineers face incompleteness and incoherency problems in the data. Probabilistic tools badly handle these kinds of problems...
Christophe Simon, Philippe Weber