Bayesian & Probabilistic

Discriminative Transfer Learning with Tree-based Priors NeurIPS 2013 Domain Adaptation under Target and Conditional Shift ICML 2013 Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture NeurIPS 2013 Dynamic Covariance Models for Multivariate Financial Time Series ICML 2013 Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks ICML 2013 EDML for Learning Parameters in Directed and Undirected Graphical Models NeurIPS 2013 Efficiently Sampling Probabilistic Programs via Program Analysis AISTATS 2013 Efficient Online Inference for Bayesian Nonparametric Relational Models NeurIPS 2013 Efficient Optimization for Sparse Gaussian Process Regression NeurIPS 2013 Embed and Project: Discrete Sampling with Universal Hashing NeurIPS 2013 Exact Learning of Bounded Tree-width Bayesian Networks AISTATS 2013 Exploiting the Power of Stereo Confidences CVPR 2013 Exploring the Mind: Integrating Questionnaires and fMRI ICML 2013 Factorial Multi-Task Learning : A Bayesian Nonparametric Approach ICML 2013 Factorized Asymptotic Bayesian Inference for Latent Feature Models NeurIPS 2013 Fast MCMC Sampling for Markov Jump Processes and Extensions JMLR 2013 Finding Optimal Bayesian Networks Using Precedence Constraints JMLR 2013 First-order Decomposition Trees NeurIPS 2013 Flexible sampling of discrete data correlations without the marginal distributions NeurIPS 2013 Forgetful Bayes and myopic planning: Human learning and decision-making in a bandit setting NeurIPS 2013 Gaussian Kullback-Leibler Approximate Inference JMLR 2013 Gaussian Process Conditional Copulas with Applications to Financial Time Series NeurIPS 2013 Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013 Generalized Random Utility Models with Multiple Types NeurIPS 2013 Geometric optimisation on positive definite matrices for elliptically contoured distributions NeurIPS 2013