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Probabilistic Modeling

1884 directly classified papers

Papers per year

Papers

Learning Gaussian Graphical Models with Observed or Latent FVSs NIPS 2013
Tracking Time-varying Graphical Structure NIPS 2013
Scalable Inference for Logistic-Normal Topic Models NIPS 2013
Demixing odors - fast inference in olfaction NIPS 2013
Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NIPS 2013
Projecting Ising Model Parameters for Fast Mixing NIPS 2013
Modeling Overlapping Communities with Node Popularities NIPS 2013
Bayesian inference for low rank spatiotemporal neural receptive fields NIPS 2013
Universal models for binary spike patterns using centered Dirichlet processes NIPS 2013
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach NIPS 2013
Bayesian Mixture Modelling and Inference based Thompson Sampling in Monte-Carlo Tree Search NIPS 2013
Sensor Selection in High-Dimensional Gaussian Trees with Nuisances NIPS 2013
Multiscale Dictionary Learning for Estimating Conditional Distributions NIPS 2013
Real-Time Inference for a Gamma Process Model of Neural Spiking NIPS 2013
Documents as multiple overlapping windows into grids of counts NIPS 2013
Machine Teaching for Bayesian Learners in the Exponential Family NIPS 2013
Flexible sampling of discrete data correlations without the marginal distributions NIPS 2013
Designed Measurements for Vector Count Data NIPS 2013
What do row and column marginals reveal about your dataset? NIPS 2013
Message Passing Inference with Chemical Reaction Networks NIPS 2013
Spike train entropy-rate estimation using hierarchical Dirichlet process priors NIPS 2013
Using multiple samples to learn mixture models NIPS 2013
First-order Decomposition Trees NIPS 2013
Approximate inference in latent Gaussian-Markov models from continuous time observations NIPS 2013
Lexical and Hierarchical Topic Regression NIPS 2013