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103
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COGSCI
2010
99views more  COGSCI 2010»
15 years 27 days ago
Learning to Learn Causal Models
Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical B...
Charles Kemp, Noah D. Goodman, Joshua B. Tenenbaum
92
Voted
CGF
2008
143views more  CGF 2008»
15 years 27 days ago
Sketch-Based Procedural Surface Modeling and Compositing Using Surface Trees
We present a system for creating and manipulating layered procedural surface editing operations, which is motivated by the limited support for iterative design in free-form modeli...
Ryan Schmidt, Karan Singh
112
Voted
NECO
2002
145views more  NECO 2002»
15 years 14 days ago
Bayesian Model Assessment and Comparison Using Cross-Validation Predictive Densities
In this work, we discuss practical methods for the assessment, comparison, and selection of complex hierarchical Bayesian models. A natural way to assess the goodness of the model...
Aki Vehtari, Jouko Lampinen
CVPR
2006
IEEE
16 years 2 months ago
Multiple Object Class Detection with a Generative Model
In this paper we propose an approach capable of simultaneous recognition and localization of multiple object classes using a generative model. A novel hierarchical representation ...
Krystian Mikolajczyk, Bastian Leibe, Bernt Schiele
100
Voted
CVPR
2008
IEEE
16 years 2 months ago
A discriminatively trained, multiscale, deformable part model
This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...