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» Bootstrap learning of foundational representations
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SYNTHESE
2010
70views more  SYNTHESE 2010»
13 years 2 months ago
Models and fiction
Most scientific models are not physical objects, and this raises important questions. What sort of entity are models, what is truth in a model, and how do we learn about models? In...
Roman Frigg
C5
2008
IEEE
14 years 1 months ago
Toward A More Scalable End-User Scripting Language
End-user scripting languages are relatively easy to learn, but have limited expressive power. Tile-based scripting systems are particularly accessible to beginners, but usually ar...
Alessandro Warth, Takashi Yamamiya, Yoshiki Ohshim...
AI
2008
Springer
13 years 6 months ago
MEBN: A language for first-order Bayesian knowledge bases
Although classical first-order logic is the de facto standard logical foundation for artificial intelligence, the lack of a built-in, semantically grounded capability for reasonin...
Kathryn B. Laskey
JMLR
2010
140views more  JMLR 2010»
13 years 2 months ago
Mean Field Variational Approximation for Continuous-Time Bayesian Networks
Continuous-time Bayesian networks is a natural structured representation language for multicomponent stochastic processes that evolve continuously over time. Despite the compact r...
Ido Cohn, Tal El-Hay, Nir Friedman, Raz Kupferman
ICML
2010
IEEE
13 years 8 months ago
Continuous-Time Belief Propagation
Many temporal processes can be naturally modeled as a stochastic system that evolves continuously over time. The representation language of continuous-time Bayesian networks allow...
Tal El-Hay, Ido Cohn, Nir Friedman, Raz Kupferman