conftrace_

graphical model

864 papers

Explore in graph

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

A Principled Deep Random Field Model for Image Segmentation CVPR 2013
A Fully-Connected Layered Model of Foreground and Background Flow CVPR 2013
Uncertainty-Driven Efficiently-Sampled Sparse Graphical Models for Concurrent Tumor Segmentation and Atlas Registration ICCV 2013
Projecting Ising Model Parameters for Fast Mixing NIPS 2013
On the Complexity and Approximation of Binary Evidence in Lifted Inference NIPS 2013
Human Pose Estimation Using a Joint Pixel-wise and Part-wise Formulation CVPR 2013
Universality of the Local Marginal Polytope CVPR 2013
BIG & QUIC: Sparse Inverse Covariance Estimation for a Million Variables NIPS 2013
Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models NIPS 2013
Latent Structured Active Learning NIPS 2013
Linear Approximation to ADMM for MAP inference ACML 2013
Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs ICML 2013
SADA: A General Framework to Support Robust Causation Discovery ICML 2013
Taming the Curse of Dimensionality: Discrete Integration by Hashing and Optimization ICML 2013
Markov Network Estimation From Multi-attribute Data ICML 2013
The Most Generative Maximum Margin Bayesian Networks ICML 2013
Hierarchical Tensor Decomposition of Latent Tree Graphical Models ICML 2013
Learning Convex QP Relaxations for Structured Prediction ICML 2013
Dynamical And-Or Graph Learning for Object Shape Modeling and Detection NIPS 2012
Learning Linear Cyclic Causal Models with Latent Variables JMLR 2012
Minimization of Continuous Bethe Approximations: A Positive Variation NIPS 2012
Discriminative Learning of Sum-Product Networks NIPS 2012
High-dimensional Sparse Inverse Covariance Estimation using Greedy Methods AISTATS 2012
High-Dimensional Structured Feature Screening Using Binary Markov Random Fields AISTATS 2012
DARWIN: A Framework for Machine Learning and Computer Vision Research and Development JMLR 2012