Probabilistic Modeling

Collapsed Variational Bayesian Inference for Hidden Markov Models AISTATS 2013 Completeness Results for Lifted Variable Elimination AISTATS 2013 Conditional Random Fields via Univariate Exponential Families NeurIPS 2013 Context-sensitive active sensing in humans NeurIPS 2013 Demixing odors - fast inference in olfaction NeurIPS 2013 Discovering Hidden Variables in Noisy-Or Networks using Quartet Tests NeurIPS 2013 Domain Adaptation under Target and Conditional Shift ICML 2013 Dynamic Clustering via Asymptotics of the Dependent Dirichlet Process Mixture NeurIPS 2013 Dynamic Probabilistic Models for Latent Feature Propagation in Social Networks ICML 2013 Efficiently Sampling Probabilistic Programs via Program Analysis AISTATS 2013 Efficient Optimization for Sparse Gaussian Process Regression NeurIPS 2013 Embed and Project: Discrete Sampling with Universal Hashing 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 Gaussian Kullback-Leibler Approximate Inference JMLR 2013 Gaussian Process Vine Copulas for Multivariate Dependence ICML 2013 Geometric optimisation on positive definite matrices for elliptically contoured distributions NeurIPS 2013 Hidden Factor Analysis for Age Invariant Face Recognition ICCV 2013 Inferring "Dark Matter" and "Dark Energy" from Videos ICCV 2013 Infinite Latent Conditional Random Fields for Modeling Environments through Humans RSS 2013 Integrated Non-Factorized Variational Inference NeurIPS 2013 Kernel Bayes' Rule: Bayesian Inference with Positive Definite Kernels JMLR 2013 Latent Data Association: Bayesian Model Selection for Multi-target Tracking ICCV 2013