'Gaussian models' diaporamas de présentation

Meta-Regression & Mixed Effects

533 views • 36 slides

Using Bayesian Networks to Analyze Expression Data

365 views • 28 slides

Gaussian Mixture Models and Acoustic Modeling

Gaussian Mixture Models and Acoustic Modeling. Lecture 9 Spoken Language Processing Prof. Andrew Rosenberg. Acoustic Modeling. The goal of the Acoustic Model is to hypothesize a phone label based on acoustic observations .

717 views • 27 slides

Gesture recognition using salience detection and concatenated HMMs

Gesture recognition using salience detection and concatenated HMMs. Ying Yin yingyin@csail.mit.edu Randall Davis davis@csail.mit.edu Massachusetts Institute of Technology. System overview. Feature vector sequence. Depth & RGB images. Hand tracking. Hand movement segmentation. Xsens

345 views • 23 slides

Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks

Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. -Arnaud Doucet, Nando de Freitas et al, UAI 2000-. outline. Introduction Problem Formulation Importance Sampling and Rao-Blackwellisation Rao-Blackwellisation Particle Filter Example Conclusion. Introduction.

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Novel approach to nonlinear/non-Gaussian Bayesian state estimation

Novel approach to nonlinear/non-Gaussian Bayesian state estimation. N.J Gordon, D.J. Salmond and A.F.M. Smith. Presenter: Tri Tran 7-2005. Outline. Motivations Recursive Bayesian estimations Bayesian Bootstrap filter algorithms Evaluations of the algorithms Summary. Motivations.

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CSSE463: Image Recognition Day 2

CSSE463: Image Recognition Day 2. Roll call Announcements: Reinstall Matlab if you are having problems: Lab 1 has directions . Angel has drop box for Lab 1 Bonus points to first person to find errors in course materials ! Tomorrow: more Matlab how-to ( bring laptop)

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Assimilated Meteorological Data

Assimilated Meteorological Data. 8 th Modeling Conference RTP, NC. Constraints on Assimilated Data. Will use of assimilated data allow more accurate modeled results? Is added cost worth it? Data is chronological (1tb/yr.); users need data geographically.

107 views • 10 slides