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» Network Engineering for Complex Belief Networks
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IROS
2008
IEEE
138views Robotics» more  IROS 2008»
14 years 1 months ago
Deep belief net learning in a long-range vision system for autonomous off-road driving
Abstract— We present a learning-based approach for longrange vision that is able to accurately classify complex terrain at distances up to the horizon, thus allowing high-level s...
Raia Hadsell, Ayse Erkan, Pierre Sermanet, Marco S...
CEC
2009
IEEE
14 years 2 months ago
Bio-inspired reverse engineering of regulatory networks
— Regulatory networks are complex networks. This paper addresses the challenge of modelling these networks. The Boolean representation is chosen and supported as a representation...
Cristina Costa Santini, Gunnar Tufte, Pauline C. H...
IJAR
2008
167views more  IJAR 2008»
13 years 7 months ago
Approximate algorithms for credal networks with binary variables
This paper presents a family of algorithms for approximate inference in credal networks (that is, models based on directed acyclic graphs and set-valued probabilities) that contai...
Jaime Shinsuke Ide, Fabio Gagliardi Cozman
NIPS
2007
13 years 8 months ago
Discovering Weakly-Interacting Factors in a Complex Stochastic Process
Dynamic Bayesian networks are structured representations of stochastic processes. Despite their structure, exact inference in DBNs is generally intractable. One approach to approx...
Charlie Frogner, Avi Pfeffer
AAAI
2006
13 years 8 months ago
An Edge Deletion Semantics for Belief Propagation and its Practical Impact on Approximation Quality
We show in this paper that the influential algorithm of iterative belief propagation can be understood in terms of exact inference on a polytree, which results from deleting enoug...
Arthur Choi, Adnan Darwiche