Probabilistic Modeling

Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference NeurIPS 2015 Preference Relation-based Markov Random Fields for Recommender Systems ACML 2015 Principal Differences Analysis: Interpretable Characterization of Differences between Distributions NeurIPS 2015 Probabilistic Appearance Models for Segmentation and Classification ICCV 2015 Probabilistic Curve Learning: Coulomb Repulsion and the Electrostatic Gaussian Process NeurIPS 2015 Probabilistic Variational Bounds for Graphical Models NeurIPS 2015 Probability Occupancy Maps for Occluded Depth Images CVPR 2015 Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood ICML 2015 Recovering Communities in the General Stochastic Block Model Without Knowing the Parameters NeurIPS 2015 Reified Context Models ICML 2015 Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process AISTATS 2015 Rent3D: Floor-Plan Priors for Monocular Layout Estimation CVPR 2015 Rethinking LDA: Moment Matching for Discrete ICA NeurIPS 2015 Robust Multi-Image Based Blind Face Hallucination CVPR 2015 Sampling from Probabilistic Submodular Models NeurIPS 2015 Scalable Deep Poisson Factor Analysis for Topic Modeling ICML 2015 Scalable Inference for Gaussian Process Models with Black-Box Likelihoods NeurIPS 2015 Smooth and Strong: MAP Inference with Linear Convergence NeurIPS 2015 Softstar: Heuristic-Guided Probabilistic Inference NeurIPS 2015 Sparse Submodular Probabilistic PCA AISTATS 2015 Stochastic Spectral Descent for Restricted Boltzmann Machines AISTATS 2015 Structural Maxent Models ICML 2015 Tractable Learning for Complex Probability Queries NeurIPS 2015 Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy NeurIPS 2015 Transformation of Markov Random Fields for Marginal Distribution Estimation CVPR 2015