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Distributed Message Passing for Large Scale Graphical Models

This code of our CVPR11 paper implements distributed convex belief propagation (BP). It works for all platforms and general graphs with potentials of arbitrary order. The code can be found here

 

Efficient Large-Scale Stereo Matching

The code for our ACCV10 paper can be found here

 

Learning to Recognize Objects from Unseen Modalities

The code for our ECCV10 paper can be found here

 

Non-linear Matrix Factorization with Gaussian Processes

The code for our ICML09 paper can be found here

 

Discriminative GPLVM

An implementation of our ICML07 paper can be found on Neil Lawrence GPLVM toobox here

 

Local Gaussian Process Regression

Coming soon code for our CVPR08 paper ...


 


 



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Prof. Raquel Urtasun

Address:
Toyota Technological Institute at Chicago
6045 S. Kenwood Ave.
Chicago, IL 60637

Phone: +1 (773) 834-2550
Email: rurtasun (at) ttic (dot) edu Fax: +1 (773) 834-9881

 


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