Bayesian robot system identification with input and output noise

Source URL: www-clmc.usc.edu

Scalable Bayesian learning for complex data Alan Qi Purdue CS & Statistics Joint work with F. Yan, Z. Xu, T.P. Minka, R. Xiang

Source URL: www.cs.purdue.edu

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

Emulation of higher-order tensors in manifold Monte Carlo methods for Bayesian Inverse Problems

Source URL: users.ices.utexas.edu

Bayesian Combination of Multiple, Imperfect Classifiers Edwin Simpson, Stephen Roberts Department of Engineering Science, University of Oxford, UK. Arfon Smith , Chris Lintott Department of Physics, University of Oxford,

Source URL: www.orchid.ac.uk

Estimating Import Demand Functions in Major Beef Importing Countries by Bayesian Hierarchical Linear Model Byung Min Soon, Department of Agricultural and Applied Economics, University of Missouri,

Source URL: ageconsearch.umn.edu

Nonparametric Bayesian Statistics Tamara Broderick ITT Career Development Assistant Professor Electrical Engineering & Computer Science MIT

Source URL: www.tamarabroderick.com

Forum Probabilistic models, learning algorithms, and response variability: sampling in cognitive development Elizabeth Bonawitz1, Stephanie Denison2, Thomas L. Griffiths3, and Alison Gopnik3

Source URL: ccdlab.rutgers.edu

• Statistical inference
• Statistical theory
• Philosophy of science
• Sampling techniques
• Psychometrics
• Bayesian inference
• Statistics
• Monte Carlo method
• Statistical hypothesis testing
• Sampling
• Causality
• Bayesian network

Psychological Review 2013, Vol. 120, No. 4, 817– 851 © 2013 American Psychological Association 0033-295X/13/$12.00 DOI: a0034194

Source URL: cocosci.berkeley.edu

• Machine learning
• Statistics
• Cybernetics
• Learning
• Image segmentation
• Feature learning
• Bayesian inference
• Cognition
• One-shot learning
• Concept learning

Teaching Ambiguous Evidence 1 Teaching three-and-a-half-year-olds to revise their beliefs given ambiguous evidence Elizabeth B. Bonawitz1, Adina Fischer2, & Laura Schulz3 1

Source URL: eccl.mit.edu

• Philosophy
• Epistemology
• Logic
• Causal inference
• Reasoning
• Design of experiments
• Philosophy of science
• Causality
• Theory-theory
• Inductive reasoning
• Bayesian inference
• Belief