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» Latent Variable Models for Causal Knowledge Acquisition
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ICIP
2007
IEEE
16 years 2 months ago
Monocular Tracking 3D People By Gaussian Process Spatio-Temporal Variable Model
Tracking 3D people from monocular video is often poorly constrained. To mitigate this problem, prior knowledge should be exploited. In this paper, the Gaussian process spatio-temp...
Junbiao Pang, Laiyun Qing, Qingming Huang, Shuqian...
100
Voted
AAAI
2006
15 years 1 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
126
Voted
PKDD
2010
Springer
148views Data Mining» more  PKDD 2010»
14 years 10 months ago
Exploiting Causal Independence in Markov Logic Networks: Combining Undirected and Directed Models
Abstract. A new method is proposed for compiling causal independencies into Markov logic networks (MLNs). An MLN can be viewed as compactly representing a factorization of a joint ...
Sriraam Natarajan, Tushar Khot, Daniel Lowd, Prasa...
110
Voted
ECCV
2010
Springer
15 years 5 months ago
Inferring 3D Shapes and Deformations from Single Views
Abstract. In this paper we propose a probabilistic framework that models shape variations and infers dense and detailed 3D shapes from a single silhouette. We model two types of sh...
CSB
2003
IEEE
130views Bioinformatics» more  CSB 2003»
15 years 5 months ago
Latent Structure Models for the Analysis of Gene Expression Data
Cluster methods have been successfully applied in gene expression data analysis to address tumor classification. By grouping tissue samples into homogeneous subsets, more systema...
Dong Hua, Dechang Chen, Xiuzhen Cheng, Abdou Youss...