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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Segmental Hidden Markov Models with Random Effects for Waveform Modeling JMLR 2006
Context Effects in Category Learning: An Investigation of Four Probabilistic Models NIPS 2006
Stratification Learning: Detecting Mixed Density and Dimensionality in High Dimensional Point Clouds NIPS 2006
A Bayesian Approach to Diffusion Models of Decision-Making and Response Time NIPS 2006
Isotonic Conditional Random Fields and Local Sentiment Flow NIPS 2006
Detecting Humans via Their Pose NIPS 2006
Generalized Bradley-Terry Models and Multi-Class Probability Estimates JMLR 2006
Distributed Inference in Dynamical Systems NIPS 2006
A Switched Gaussian Process for Estimating Disparity and Segmentation in Binocular Stereo 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
Linear State-Space Models for Blind Source Separation JMLR 2006
Estimating Functions for Blind Separation When Sources Have Variance Dependencies JMLR 2005
Expectation Consistent Approximate Inference JMLR 2005
Local Propagation in Conditional Gaussian Bayesian Networks JMLR 2005
Estimation of Non-Normalized Statistical Models by Score Matching JMLR 2005
Learning Module Networks JMLR 2005
The Minimum Error Minimax Probability Machine JMLR 2004