<--- Back to Details
First PageDocument Content
Statistical models / Machine learning / Bayesian statistics / Cluster analysis / Mixture model / Pattern recognition / Graphical model / Bayesian network / Probabilistic logic / Principal component analysis / Expectationmaximization algorithm / Probability distribution
Date: 2011-09-30 17:04:00
Statistical models
Machine learning
Bayesian statistics
Cluster analysis
Mixture model
Pattern recognition
Graphical model
Bayesian network
Probabilistic logic
Principal component analysis
Expectationmaximization algorithm
Probability distribution

Probabilistic Reasoning for Assembly-Based 3D Modeling

Add to Reading List

Source URL: geometry.stanford.edu

Download Document from Source Website

File Size: 3,05 MB

Share Document on Facebook

Similar Documents

Statistical classification / Statistics / Probability and statistics / Mathematics / Support vector machine / Predictive modelling / K-nearest neighbors algorithm / Mathematical model / Data analysis / Spatial analysis / Regression analysis / Artificial neural network

Visualizing statistical models: Removing the blindfold Hadley Wickham, Dianne Cook and Heike Hofmann Department of Statistics MSMain St Houston TXe-mail:

DocID: 1xVjw - View Document

Estimation theory / Econometrics / Statistical inference / Estimator / Probability distribution fitting / M-estimators / Maximum likelihood estimation / Fisher information / Gamma distribution / Maximum spacing estimation

Noise-contrastive estimation: A new estimation principle for unnormalized statistical models Michael Gutmann Dept of Computer Science and HIIT, University of Helsinki

DocID: 1xUlB - View Document

Code Completion with Statistical Language Models Veselin Raychev Martin Vechev Eran Yahav

DocID: 1xToM - View Document

An Introduction to the Statistical Analysis of Agent-Based Models Giorgio Fagiolo https://mail.sssup.it/~fagiolo

DocID: 1vhKi - View Document

FallSTA4513: Statistical Models of Networks Lecture 3 — 24 September, 2014 Prof. Daniel M. Roy

DocID: 1vfwF - View Document