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» Bayesian inference for differential equations
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ICCV
2005
IEEE
14 years 2 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
EH
2002
IEEE
139views Hardware» more  EH 2002»
14 years 1 months ago
Evolving Cellular Automata to Model Fluid Flow in Porous Media
Fluid flow in porous media is a dynamic process that is traditionally modeled using PDE (Partial Differential Equations). In this approach, physical properties related to fluid fl...
Tina Yu, Seong Lee
IAT
2008
IEEE
14 years 3 months ago
Finding Minimum Data Requirements Using Pseudo-independence
In situations where Bayesian networks (BN) inferencing approximation is allowable, we show how to reduce the amount of sensory observations necessary and in a multi-agent context ...
Yoonheui Kim, Victor R. Lesser
CVIU
2006
158views more  CVIU 2006»
13 years 8 months ago
Sequential mean field variational analysis of structured deformable shapes
A novel approach is proposed to analyzing and tracking the motion of structured deformable shapes, which consist of multiple correlated deformable subparts. Since this problem is ...
Gang Hua, Ying Wu
BMCBI
2010
125views more  BMCBI 2010»
13 years 3 months ago
ProbFAST: Probabilistic Functional Analysis System Tool
Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered...
Israel T. da Silva, Ricardo Z. N. Vêncio, Th...