Bayesian Inference

Optimising Kernel Parameters and Regularisation Coefficients for Non-linear Discriminant Analysis JMLR 2006 PAC-Bayes Bounds for the Risk of the Majority Vote and the Variance of the Gibbs Classifier NeurIPS 2006 Parameter Expanded Variational Bayesian Methods NeurIPS 2006 Particle Filtering for Nonparametric Bayesian Matrix Factorization NeurIPS 2006 Real-time adaptive information-theoretic optimization of neurophysiology experiments NeurIPS 2006 Sparse Multinomial Logistic Regression via Bayesian L1 Regularisation NeurIPS 2006 Stochastic Complexities of Gaussian Mixtures in Variational Bayesian Approximation JMLR 2006 The Identity Management Kalman Filter (IMKF) RSS 2006 The Iterated Sigma Point Kalman Filter with Applications to Long Range Stereo RSS 2006 The Neurodynamics of Belief Propagation on Binary Markov Random Fields NeurIPS 2006 Theory and Dynamics of Perceptual Bistability NeurIPS 2006 Tighter PAC-Bayes Bounds NeurIPS 2006 TrueSkill™: A Bayesian Skill Rating System NeurIPS 2006 Unified Inference for Variational Bayesian Linear Gaussian State-Space Models NeurIPS 2006 Unified Inverse Depth Parametrization for Monocular SLAM RSS 2006 Using Combinatorial Optimization within Max-Product Belief Propagation NeurIPS 2006 Walk-Sums and Belief Propagation in Gaussian Graphical Models JMLR 2006 A Bayesian Model for Supervised Clustering with the Dirichlet Process Prior JMLR 2005 A Bayes Optimal Approach for Partitioning the Values of Categorical Attributes JMLR 2005 Assessing Approximate Inference for Binary Gaussian Process Classification JMLR 2005 Asymptotic Model Selection for Naive Bayesian Networks JMLR 2005 Denoising Source Separation JMLR 2005 Discriminative Training of Kalman Filters RSS 2005 Expectation Consistent Approximate Inference JMLR 2005 Inner Product Spaces for Bayesian Networks JMLR 2005