probabilistic inference

Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks NeurIPS 2016 New Liftable Classes for First-Order Probabilistic Inference NeurIPS 2016 Optimality of Belief Propagation for Crowdsourced Classification ICML 2016 Probabilistic Approximate Least-Squares AISTATS 2016 Probabilistic Inference with Generating Functions for Poisson Latent Variable Models NeurIPS 2016 Scalable MAP inference in Bayesian networks based on a Map-Reduce approach PGM 2016 Solving Marginal MAP Problems with NP Oracles and Parity Constraints NeurIPS 2016 Synthesis of MCMC and Belief Propagation NeurIPS 2016 The Effect of Combination Functions on the Complexity of Relational Bayesian Networks PGM 2016 Unsupervised Learning of 3D Structure from Images NeurIPS 2016 Variable Elimination in the Fourier Domain ICML 2016 A Hybrid Approach for Probabilistic Inference using Random Projections ICML 2015 A Linear Dynamical System Model for Text ICML 2015 Decomposition Bounds for Marginal MAP NeurIPS 2015 Exploiting Symmetries to Construct Efficient MCMC Algorithms With an Application to SLAM AISTATS 2015 Fast Lifted MAP Inference via Partitioning NeurIPS 2015 Latent Trees for Estimating Intensity of Facial Action Units CVPR 2015 On the Relationship between Sum-Product Networks and Bayesian Networks ICML 2015 Pushing Forward Marginal MAP with Best-First Search IJCAI 2015 Softstar: Heuristic-Guided Probabilistic Inference NeurIPS 2015 Submodular Point Processes with Applications to Machine learning AISTATS 2015 Synaptic Sampling: A Bayesian Approach to Neural Network Plasticity and Rewiring NeurIPS 2015 Tractable Learning for Complex Probability Queries NeurIPS 2015 Transformation of Markov Random Fields for Marginal Distribution Estimation CVPR 2015 An inclusion optimal algorithm for chain graph structure learning AISTATS 2014