conftrace_

graphical model

864 papers

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Also known as

GM

Co-occurring keywords

structure learning (341) causal inference (1630) bayesian network (378) causal discovery (460) probabilistic inference (312) belief propagation (177) approximate inference (253) probabilistic modeling (852) bayesian inference (1907) markov random field (303)

Papers

libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models JMLR 2010
The Hidden Life of Latent Variables: Bayesian Learning with Mixed Graph Models JMLR 2009
Estimation of Sparse Binary Pairwise Markov Networks using Pseudo-likelihoods JMLR 2009
Approximating MAP by Compensating for Structural Relaxations NIPS 2009
The Nonparanormal: Semiparametric Estimation of High Dimensional Undirected Graphs JMLR 2009
An Algorithm for Reading Dependencies from the Minimal Undirected Independence Map of a Graphoid that Satisfies Weak Transitivity JMLR 2009
Controlling the False Discovery Rate of the Association/Causality Structure Learned with the PC Algorithm JMLR 2009
Learning from Neighboring Strokes: Combining Appearance and Context for Multi-Domain Sketch Recognition NIPS 2009
Local Rules for Global MAP: When Do They Work ? NIPS 2009
Learning a Small Mixture of Trees NIPS 2009
Localizing Bugs in Program Executions with Graphical Models NIPS 2009
Time-Varying Dynamic Bayesian Networks NIPS 2009
Riffled Independence for Ranked Data NIPS 2009
An LP View of the M-best MAP problem NIPS 2009
Conditional Random Fields with High-Order Features for Sequence Labeling NIPS 2009
Accelerating Bayesian Structural Inference for Non-Decomposable Gaussian Graphical Models NIPS 2009
Graph Zeta Function in the Bethe Free Energy and Loopy Belief Propagation NIPS 2009
FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs NIPS 2009
Perceptual Multistability as Markov Chain Monte Carlo Inference NIPS 2009
Sparse and Locally Constant Gaussian Graphical Models NIPS 2009
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data NIPS 2009
Bayesian Nonparametric Models on Decomposable Graphs NIPS 2009
Which graphical models are difficult to learn? NIPS 2009
Graphical Methods for Efficient Likelihood Inference in Gaussian Covariance Models JMLR 2008
Robust Near-Isometric Matching via Structured Learning of Graphical Models NIPS 2008