Complexity of Inference in Graphical Models Venkat Chandrasekaran Laboratory for Information and Decision Systems Massachusetts Institute of Technology Cambridge, MA 02139

Source URL: uai2008.cs.helsinki.fi

Graphical Models—Errata Steffen L. Lauritzen University of Oxford June 7, 2011 Abstract This note identifies some of the known typographical and other

Source URL: www.stats.ox.ac.uk

Incremental Knowledge Base Construction Using DeepDive Jaeho Shin† Sen Wu†

Source URL: i.stanford.edu

• Logic
• Philosophy
• Graphical models
• Epistemology
• Statistical inference
• Inference
• Logical consequence
• Reasoning
• Bayesian inference
• Data transformation
• Belief propagation
• Causality

In: (Balakrishnan, N. et al., eds) Wiley StatsRef: Statistics Reference Online (2015); to appear. Graphical Markov models, unifying results and their interpretation Nanny Wermuth

Source URL: www.math.chalmers.se

Leveraging Graphical Models to Improve Accuracy and Reduce Privacy Risks of Mobile Sensing Abhinav Parate Meng-Chieh Chiu

Source URL: people.cs.umass.edu

Semantic Segmentation With Object Clique Potentials Xiaojuan Qi Jianping Shi Shu Liu Renjie Liao The Chinese University of Hong Kong

Source URL: www.cse.cuhk.edu.hk

• Artificial intelligence
• Computational neuroscience
• Computer vision
• Cybernetics
• Applied mathematics
• Image segmentation
• Convolutional neural network
• Graphical models
• Outline of object recognition
• Conference on Computer Vision and Pattern Recognition
• Conditional random field
• Initial and terminal objects

GraMSec’15 – CFP The Second International Workshop on Graphical Models for Security July 13, 2015, Verona, Italy http://gramsec.uni.lu (Co-located with CSF 2015)

Source URL: gramsec.uni.lu

Variational Inference with Normalizing Flows Danilo Jimenez Rezende Shakir Mohamed Google DeepMind, London

Source URL: jmlr.org

• Statistics
• Probability
• Statistical models
• Graphical models
• Probability distributions
• Variational Bayesian methods
• Bayesian network
• Expectationmaximization algorithm
• Normal distribution
• Mixture model
• Exponential family
• Bayesian inference

Bayesian Networks and Graphical Models with R Tutorial given at the useR! 2015 conference in Aalborg, Denmark Presenters: Søren Højsgaard, Department of Mathematical Sciences, Aalborg University, Denmark and Therese Gr

Source URL: user2015.math.aau.dk

EXACT FORMULAS FOR THE NORMALIZING CONSTANTS OF WISHART DISTRIBUTIONS FOR GRAPHICAL MODELS By Caroline Uhler∗ , Alex Lenkoski† , and Donald Richards§ IST Austria∗ , Norwegian Computing Center† , Heidelberg Unive

Source URL: www.carolineuhler.com