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» Variational Inference for Diffusion Processes
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ICIAP
2003
ACM
14 years 7 months ago
Dense 3D interpretation of image sequences: a variational approach using anisotropic diffusion
The purpose of this study is to investigate a new method for recovering relative depth and 3D motion from a temporal sequence of monocular images. The method is direct insomuch as...
Hicham Sekkati, Amar Mitiche
ICML
2004
IEEE
14 years 8 months ago
Variational methods for the Dirichlet process
Variational inference methods, including mean field methods and loopy belief propagation, have been widely used for approximate probabilistic inference in graphical models. While ...
David M. Blei, Michael I. Jordan
DAGM
2006
Springer
13 years 11 months ago
Diffusion-Like Reconstruction Schemes from Linear Data Models
In this paper we extend anisotropic diffusion with a diffusion tensor to be applicable to data that is well modeled by linear models. We focus on its variational theory, and invest...
Hanno Scharr
KDD
2010
ACM
188views Data Mining» more  KDD 2010»
13 years 9 months ago
Inferring networks of diffusion and influence
Information diffusion and virus propagation are fundamental processes talking place in networks. While it is often possible to directly observe when nodes become infected, observi...
Manuel Gomez-Rodriguez, Jure Leskovec, Andreas Kra...
ICASSP
2011
IEEE
12 years 11 months ago
Sequential Monte Carlo method for parameter estimation in diffusion models of affinity-based biosensors
Estimation of the amounts of target molecules in realtime affinity-based biosensors is studied. The problem is mapped to inferring the parameters of a temporally sampled diffusio...
Manohar Shamaiah, Xiaohu Shen, Haris Vikalo