Bayesian & Probabilistic

Kernel Measures of Conditional Dependence NeurIPS 2007 Learning Visual Attributes NeurIPS 2007 Learning with Tree-Averaged Densities and Distributions NeurIPS 2007 Local Algorithms for Approximate Inference in Minor-Excluded Graphs NeurIPS 2007 Loop Series and Bethe Variational Bounds in Attractive Graphical Models NeurIPS 2007 Markov Chain Monte Carlo with People NeurIPS 2007 Measuring Neural Synchrony by Message Passing NeurIPS 2007 Modeling homophily and stochastic equivalence in symmetric relational data NeurIPS 2007 Modeling Natural Sounds with Modulation Cascade Processes NeurIPS 2007 Modelling motion primitives and their timing in biologically executed movements NeurIPS 2007 Multi-task Gaussian Process Prediction NeurIPS 2007 Multi-Task Learning for Classification with Dirichlet Process Priors JMLR 2007 Near-Maximum Entropy Models for Binary Neural Representations of Natural Images NeurIPS 2007 Neural characterization in partially observed populations of spiking neurons NeurIPS 2007 New Outer Bounds on the Marginal Polytope NeurIPS 2007 Non-parametric Modeling of Partially Ranked Data NeurIPS 2007 People Tracking with the Laplacian Eigenmaps Latent Variable Model NeurIPS 2007 Predictive Matrix-Variate t Models NeurIPS 2007 Privacy-Preserving Belief Propagation and Sampling NeurIPS 2007 Probabilistic Matrix Factorization NeurIPS 2007 Receptive Fields without Spike-Triggering NeurIPS 2007 Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach NeurIPS 2007 Robust Regression with Twinned Gaussian Processes NeurIPS 2007 Scene Segmentation with CRFs Learned from Partially Labeled Images NeurIPS 2007 Selecting Observations against Adversarial Objectives NeurIPS 2007