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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Approximate inference for the loss-calibrated Bayesian AISTATS 2011
Hidden-Unit Conditional Random Fields AISTATS 2011
Learning mixtures of Gaussians with maximum-a-posteriori oracle AISTATS 2011
Mixed Cumulative Distribution Networks AISTATS 2011
Kernel Belief Propagation AISTATS 2011
Collective Graphical Models NIPS 2011
Parallel Gibbs Sampling: From Colored Fields to Thin Junction Trees AISTATS 2011
Anatomically Constrained Decoding of Finger Flexion from Electrocorticographic Signals NIPS 2011
Spectral Methods for Learning Multivariate Latent Tree Structure NIPS 2011
Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories NIPS 2011
Automated Refinement of Bayes Networks' Parameters based on Test Ordering Constraints NIPS 2011
Sparse Inverse Covariance Matrix Estimation Using Quadratic Approximation NIPS 2011
Dependent Indian Buffet Processes AISTATS 2010
Brain covariance selection: better individual functional connectivity models using population prior NIPS 2010
Probabilistic Deterministic Infinite Automata NIPS 2010
Approximate inference in continuous time Gaussian-Jump processes NIPS 2010
Gaussian sampling by local perturbations NIPS 2010
Global seismic monitoring as probabilistic inference NIPS 2010
Probabilistic latent variable models for distinguishing between cause and effect NIPS 2010
Shadow Dirichlet for Restricted Probability Modeling NIPS 2010
Construction of Dependent Dirichlet Processes based on Poisson Processes NIPS 2010
Deterministic Single-Pass Algorithm for LDA NIPS 2010
Modeling annotator expertise: Learning when everybody knows a bit of something AISTATS 2010
Matrix-Variate Dirichlet Process Mixture Models AISTATS 2010
Exact inference and learning for cumulative distribution functions on loopy graphs NIPS 2010