1 Event-based, 6-DOF Camera Tracking for High-Speed Applications Abstract—In contrast to standard cameras, which produce frames at a fixed rate, event cameras respond asynchronously to pixel-level brightness changes,

Source URL: rpg.ifi.uzh.ch

• Robot control
• Computer animation
• Computer vision
• Probability distributions
• Exponentials
• Exponential family
• Kalman filter
• Pose
• Normal distribution
• Variational Bayesian methods
• Motion capture
• Mixture model

16 Basic Bayesian Methods Mark E. Glickman and David A. van Dyk Summary In this chapter, we introduce the basics of Bayesian data analysis. The key ingredients to a

Source URL: www.glicko.net

• Bayesian statistics
• Bayesian inference
• Prior probability
• Beta distribution
• Likelihood function
• Statistical inference
• Normal distribution
• Confidence interval
• Posterior probability
• Conjugate prior
• Marginal likelihood

LEARNING HIDDEN VARIABLES IN PROBABILISTIC GRAPHICAL MODELS T HESIS SUBMITTED FOR THE DEGREE OF

Source URL: www.cs.huji.ac.il

• Statistical models
• Bayesian network
• Graphical model
• Nir Friedman
• Hidden variable theory
• Causality
• Expectationmaximization algorithm
• Expected value
• Latent variable

Details of our Motif Clustering Procedure 1 Bayesian Hierarchical Clustering Model The data for each discovered motif is a count matrix Ni which can have different widths and number of counts compared to other TF motifs.

Source URL: www-stat.wharton.upenn.edu

• Hierarchical clustering
• Network analysis
• Cluster analysis
• Probability distributions

Bayesian and Dominant Strategy Implementation Revisited Alex Gershkov, Benny Moldovanu and Xianwen ShiAbstract

Source URL: www.econ2.uni-bonn.de

• Database theory
• Logic

Bayesian alternatives to null-hypothesis significance testing for repeated-measures designs

Source URL: web.uvic.ca

• Statistical inference
• Hypothesis testing
• Design of experiments
• Statistical theory
• Bayesian statistics
• Statistical hypothesis testing
• Bayesian inference
• Analysis of variance
• Prior probability
• Bayes factor
• Bayes estimator
• Bayesian

Bayesian Modeling of Dependency Trees Using Hierarchical Pitman-Yor Priors Hanna M. Wallach Department of Computer Science, University of Massachusetts, Amherst, MAUSA Charles Sutton

Source URL: dirichlet.net

From Sequences to Population Parameters: Using LAMARC for Data-Mining Lucian Smith, Mary Kuhner University of Washington, Department of Genome Sciences Poster available at: http://evolution.gs.washington.edu/lamarc/Tutor

Source URL: evolution.gs.washington.edu

• Statistical inference
• Genetics
• Statistical theory
• Microsatellite
• Population genetics
• Confidence interval
• Bayesian inference
• Coalescent theory

Bayesian Optimal Control of Smoothly Parameterized Systems Yasin Abbasi-Yadkori Queensland University of Technology Abstract

Source URL: webdocs.cs.ualberta.ca

Context-Sensitive Induction Patrick Shafto1 , Charles Kemp1 , Elizabeth Baraff1 , John D. Coley2 , & Joshua B. Tenenbaum1 1 Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology 2

Source URL: ccdlab.rutgers.edu

• Reasoning
• Inductive reasoning
• Philosophy of science
• Statistical inference
• Critical thinking
• Causality
• Concept learning
• Bayesian network
• Inference
• Bayesian inference
• Theory
• Argument