# Casio Loopy

## Papers overview

Semantic Scholar uses AI to extract papers important to this topic.

Highly Cited

2011

Highly Cited

2011

- IEEE International Symposium on Information…
- 2011

We consider the estimation of a random vector observed through a linear transform followed by a componentwise probabilistic… (More)

Is this relevant?

Highly Cited

2008

Highly Cited

2008

- IEEE Transactions on Pattern Analysis and Machine…
- 2008

Among the most exciting advances in early vision has been the development of efficient energy minimization algorithms for pixel… (More)

Is this relevant?

Highly Cited

2006

Highly Cited

2006

- ECCV
- 2006

One of the most exciting advances in early vision has been the development of efficient energy minimization algorithms. Many… (More)

Is this relevant?

Highly Cited

2005

Highly Cited

2005

- Journal of Machine Learning Research
- 2005

Belief propagation (BP) is an increasingly popular method of performing approximate inference on arbitrary graphical models. At… (More)

Is this relevant?

Highly Cited

2002

Highly Cited

2002

- PODC
- 2002

In this paper, we give a theoretical analysis of peer-to-peer (P2P) networks operating in the face of concurrent joins and… (More)

Is this relevant?

Highly Cited

2001

Highly Cited

2001

- UAI
- 2001

This paper presents a new deterministic approximation technique in Bayesian networks. This method, “Expectation Propagation… (More)

Is this relevant?

Highly Cited

2001

Highly Cited

2001

- 2001

One of the major obstacles to using Bayesian methods for pattern recognition has been its computational expense. This thesis… (More)

Is this relevant?

Highly Cited

2000

Highly Cited

2000

- Neural Computation
- 2000

Graphical models, such as Bayesian networks and Markov networks, represent joint distributions over a set of variables by means… (More)

Is this relevant?

Highly Cited

1999

Highly Cited

1999

- UAI
- 1999

Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian… (More)

Is this relevant?

Highly Cited

1999

Highly Cited

1999

- Neural Computation
- 1999

Graphical models, such as Bayesian networks and Markov random fields, represent statistical dependencies of variables by a graph… (More)

Is this relevant?