Structured Determinantal Point Processes Alex Kulesza Ben Taskar Department of Computer and Information Science University of Pennsylvania Philadelphia, PA 19104

Source URL: www.seas.upenn.edu

• Mathematical analysis
• Mathematics
• Statistics
• Model theory
• Constructible universe
• Distribution
• Normal distribution
• Interpretation
• IP
• Static single assignment form

Construction of Dependent Dirichlet Processes based on Poisson Processes Dahua Lin CSAIL, MIT

Source URL: dahua.me

• Probability
• Statistics
• Stochastic processes
• Markov processes
• Probability distributions
• Poisson processes
• Markov models
• Poisson point process
• Poisson distribution
• Dirichlet process
• Mixture model
• Gibbs sampling

Coupled Dirichlet Processes: Beyond HDP John Fisher MIT CSAIL

Source URL: dahua.me

• Statistics
• Probability
• Stochastic processes
• Hierarchical Dirichlet process
• Dirichlet process
• Dirichlet distribution
• Mixture model
• Hidden Markov model
• Gibbs sampling
• Probability distribution
• Poisson point process

Estimating the sizes of populations at risk of HIV infection from multiple data sources using a Bayesian hierarchical model

Source URL: www.stat.washington.edu

• Statistics
• Statistical inference
• Mark and recapture
• Bayesian network
• Bayesian inference
• Sampling
• Beta distribution
• Interval estimation
• Point estimation
• Estimation theory

3D Shape Estimation in Video Sequences Provides High Precision Evaluation of Facial Expressions L´aszl´o A. Jeni a , Andr´as L˝orincz b , Tam´as Nagy b , Zsolt Palotai c , Judit Seb˝ok b , Zolt´an Szab´o b , D´a

Source URL: www.realeyesit.com

• Statistics
• Multivariate statistics
• Mathematics
• Data analysis
• Computer vision
• Statistical classification
• Biometrics
• Procrustes analysis
• Support vector machine
• Principal component analysis
• Point distribution model
• Norm

Penn State Astrostatistics MCMC tutorial Murali Haran, Penn State Dept. of Statistics Bayesian change point model: full conditional distributions Our goal is to draw samples from the 5-dimensional posterior distribution

Source URL: sites.stat.psu.edu

Probabilistic Seismic Casualty Models and Simplified Method to Evaluate Seismic Casualty Risk This paper discusses seismic casualty from the point of view of a probability model based on binomial distribution compared wi

Source URL: www.aij.or.jp

Behav Res DOIs13428Estimating the distribution of sensorimotor synchronization data: A Bayesian hierarchical modeling approach Rasmus Bååth 1

Source URL: www.sumsar.net

• Statistical theory
• Bayesian statistics
• Parametric statistics
• Point estimation
• Hierarchical Bayes model
• Maximum a posteriori estimation
• T-statistic
• Parameter
• Maximum likelihood
• Statistics
• Statistical inference
• Estimation theory

Calibrating a Non-isotropic Near Point Light Source using a Plane Jaesik Park1∗ Sudipta N. Sinha2 Yasuyuki Matsushita3 Yu-Wing Tai1 In So Kweon1 1

Source URL: research.microsoft.com

• Geometry
• 3D computer graphics
• Radiometry
• Virtual reality
• Blinn–Phong shading model
• Phong reflection model
• Rendering
• Specular highlight
• Bidirectional reflectance distribution function
• Computer graphics
• Shading
• Optics

The Learning Model The Learning Model illustrated here helps point out the difference between the processing functions of Active Processing and Higher Thinking Systems on the left and the storage and distribution functio

Source URL: downloads.learningrx.com

• Education
• Psychology
• G factor
• Intelligence
• Cognition
• Cognitive load
• Educational psychology
• Mind
• Cognitive science