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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

An EM Algorithm for Localizing Multiple Sound Sources in Reverberant Environments NIPS 2006
The Neurodynamics of Belief Propagation on Binary Markov Random Fields NIPS 2006
Unsupervised Learning of a Probabilistic Grammar for Object Detection and Parsing NIPS 2006
Learning to Model Spatial Dependency: Semi-Supervised Discriminative Random Fields NIPS 2006
Particle Filtering for Nonparametric Bayesian Matrix Factorization NIPS 2006
Non-rigid point set registration: Coherent Point Drift NIPS 2006
Learning Nonparametric Models for Probabilistic Imitation NIPS 2006
Statistical Modeling of Images with Fields of Gaussian Scale Mixtures NIPS 2006
Recursive Attribute Factoring NIPS 2006
Dirichlet-Enhanced Spam Filtering based on Biased Samples NIPS 2006
Learning annotated hierarchies from relational data NIPS 2006
Efficient Structure Learning of Markov Networks using $L_1$-Regularization NIPS 2006
Learning Structural Equation Models for fMRI NIPS 2006
Conditional mean field NIPS 2006
Modeling General and Specific Aspects of Documents with a Probabilistic Topic Model NIPS 2006
Multi-dynamic Bayesian Networks NIPS 2006
Uncertainty, phase and oscillatory hippocampal recall NIPS 2006
Inferring Network Structure from Co-Occurrences NIPS 2006
Clustering Under Prior Knowledge with Application to Image Segmentation NIPS 2006
Mixture Regression for Covariate Shift NIPS 2006
Learning to parse images of articulated bodies NIPS 2006
A Linear Non-Gaussian Acyclic Model for Causal Discovery JMLR 2006
Walk-Sums and Belief Propagation in Gaussian Graphical Models JMLR 2006
Distributed Inference in Dynamical Systems NIPS 2006
Context Effects in Category Learning: An Investigation of Four Probabilistic Models NIPS 2006