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Probabilistic Modeling

2591 directly classified papers

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Papers

Learning Hidden Markov Models from Non-sequence Data via Tensor Decomposition NIPS 2013
Learning Chordal Markov Networks by Constraint Satisfaction NIPS 2013
Flexible sampling of discrete data correlations without the marginal distributions NIPS 2013
Online Learning of Nonparametric Mixture Models via Sequential Variational Approximation NIPS 2013
Sensor Selection in High-Dimensional Gaussian Trees with Nuisances NIPS 2013
Σ-Optimality for Active Learning on Gaussian Random Fields NIPS 2013
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach NIPS 2013
Bayesian Estimation of Latently-grouped Parameters in Undirected Graphical Models NIPS 2013
Probabilistic Low-Rank Matrix Completion with Adaptive Spectral Regularization Algorithms NIPS 2013
Projecting Ising Model Parameters for Fast Mixing NIPS 2013
Efficient Optimization for Sparse Gaussian Process Regression NIPS 2013
Demixing odors - fast inference in olfaction NIPS 2013
Scalable Inference for Logistic-Normal Topic Models NIPS 2013
Tracking Time-varying Graphical Structure NIPS 2013
Integrated Non-Factorized Variational Inference NIPS 2013
A Graphical Transformation for Belief Propagation: Maximum Weight Matchings and Odd-Sized Cycles NIPS 2013
Approximate Gaussian process inference for the drift function in stochastic differential equations NIPS 2013
Random function priors for exchangeable arrays with applications to graphs and relational data NIPS 2012
Density Propagation and Improved Bounds on the Partition Function NIPS 2012
Fast Variational Bayesian Inference for Non-Conjugate Matrix Factorization Models AISTATS 2012
Bayesian Quadrature for Ratios AISTATS 2012
Efficient Sampling from Combinatorial Space via Bridging AISTATS 2012
Semiparametric Pseudo-Likelihood Estimation in Markov Random Fields AISTATS 2012
Lightning-speed Structure Learning of Nonlinear Continuous Networks AISTATS 2012
Topology Constraints in Graphical Models NIPS 2012