EE512A – Advanced Inference in Graphical Models — Fall Quarter, Lecture 2 — http://j.ee.washington.edu/~bilmes/classes/ee512a_fall_2014/ Prof. Jeff Bilmes University of Washington, Seattle

Source URL: j.ee.washington.edu

EE12A – Advanced Inference in Graphical Models — Fall Quarter, Lecture 1 — http://j.ee.washington.edu/~bilmes/classes/ee512a_fall_2014/ Prof. Jeff Bilmes University of Washington, Seattle

Source URL: j.ee.washington.edu

COMS  W4115  Programming  Languages  and  Translators   Fall  2014   Project  Proposal   Mehul  Shah  -­‐       EGUI  –  EASY  GRAPHICAL  

Source URL: www1.cs.columbia.edu

Intro: Graphical Models & Belief Propagation Loop Calculus: Exact Inference with BP Matching & Learning with BP Future Challenges (Loop Calculus +) Statistical Inference and Loop Calculus in

Source URL: landau100.itp.ac.ru

EE512A – Advanced Inference in Graphical Models — Fall Quarter, Lecture 10 — http://j.ee.washington.edu/~bilmes/classes/ee512a_fall_2014/ Prof. Jeff Bilmes University of Washington, Seattle

Source URL: j.ee.washington.edu

EE596A – Dynamic Graphical Models Winter Quarter 2013 Prof. Jeff Bilmes University of Washington, Seattle Department of Electrical Engineering Winter Quarter, 2013

Source URL: j.ee.washington.edu

Kernel Belief Propagation 1 Le Song,1 Arthur Gretton,1,2 Danny Bickson,1 Yucheng Low,1 Carlos Guestrin1 School of Computer Science, CMU; 2 Gatsby Computational Neuroscience Unit & MPI for Biological Cybernetics

Source URL: select.cs.cmu.edu

• Statistics
• Probability
• Mathematical analysis
• Machine learning
• Hilbert space
• Graphical models
• Probability theory
• Belief propagation
• Coding theory
• Positive-definite kernel
• Mixture model
• Normal distribution

Nonparametric Tree Graphical Models via Kernel Embeddings 1 Le Song,1 Arthur Gretton,1,2 Carlos Guestrin1 School of Computer Science, Carnegie Mellon University; 2 MPI for Biological Cybernetics

Source URL: select.cs.cmu.edu

• Mathematics
• Mathematical analysis
• Hilbert space
• Topology
• Probability theory
• Model theory
• Graphical models
• Reproducing kernel Hilbert space
• Positive-definite kernel
• Embedding
• Belief propagation
• Kalman filter

EE512A – Advanced Inference in Graphical Models — Fall Quarter, Lecture 4 — http://j.ee.washington.edu/~bilmes/classes/ee512a_fall_2014/ Prof. Jeff Bilmes University of Washington, Seattle

Source URL: j.ee.washington.edu

EE512A – Advanced Inference in Graphical Models — Fall Quarter, Lecture 18 — http://j.ee.washington.edu/~bilmes/classes/ee512a_fall_2014/ Prof. Jeff Bilmes University of Washington, Seattle

Source URL: j.ee.washington.edu