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» Causal inference using the algorithmic Markov condition
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UAI
2008
15 years 5 months ago
Causal discovery of linear acyclic models with arbitrary distributions
An important task in data analysis is the discovery of causal relationships between observed variables. For continuous-valued data, linear acyclic causal models are commonly used ...
Patrik O. Hoyer, Aapo Hyvärinen, Richard Sche...
AAAI
2008
15 years 6 months ago
Exploiting Causal Independence Using Weighted Model Counting
Previous studies have demonstrated that encoding a Bayesian network into a SAT-CNF formula and then performing weighted model counting using a backtracking search algorithm can be...
Wei Li 0002, Pascal Poupart, Peter van Beek
AAAI
2006
15 years 5 months ago
Identification of Joint Interventional Distributions in Recursive Semi-Markovian Causal Models
This paper is concerned with estimating the effects of actions from causal assumptions, represented concisely as a directed graph, and statistical knowledge, given as a probabilit...
Ilya Shpitser, Judea Pearl
PAMI
2010
238views more  PAMI 2010»
15 years 2 months ago
Tracking Motion, Deformation, and Texture Using Conditionally Gaussian Processes
—We present a generative model and inference algorithm for 3D nonrigid object tracking. The model, which we call G-flow, enables the joint inference of 3D position, orientation, ...
Tim K. Marks, John R. Hershey, Javier R. Movellan
ICGI
2004
Springer
15 years 9 months ago
Navigation Pattern Discovery Using Grammatical Inference
We present a method for modeling user navigation on a web site using grammatical inference of stochastic regular grammars. With this method we achieve better models than the previo...
Nikolaos Karampatziakis, Georgios Paliouras, Dimit...