approximate inference

t-divergence Based Approximate Inference NeurIPS 2011 Thinning Measurement Models and Questionnaire Design NeurIPS 2011 An Approximate Inference Approach to Temporal Optimization in Optimal Control NeurIPS 2010 Approximate Inference by Compilation to Arithmetic Circuits NeurIPS 2010 Approximate inference in continuous time Gaussian-Jump processes NeurIPS 2010 Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation JMLR 2010 Approximate parameter inference in a stochastic reaction-diffusion model AISTATS 2010 A Study of Approximate Inference in Probabilistic Relational Models ACML 2010 Auto-Regressive HMM Inference with Incomplete Data for Short-Horizon Wind Forecasting NeurIPS 2010 Efficient Learning of Deep Boltzmann Machines AISTATS 2010 FastInf: An Efficient Approximate Inference Library JMLR 2010 Focused Belief Propagation for Query-Specific Inference AISTATS 2010 Implicit Differentiation by Perturbation NeurIPS 2010 Importance Sampling for Continuous Time Bayesian Networks JMLR 2010 libDAI: A Free and Open Source C++ Library for Discrete Approximate Inference in Graphical Models JMLR 2010 Sidestepping Intractable Inference with Structured Ensemble Cascades NeurIPS 2010 Solving the Uncapacitated Facility Location Problem Using Message Passing Algorithms AISTATS 2010 Variational Inference over Combinatorial Spaces NeurIPS 2010 Why are DBNs sparse? AISTATS 2010 Worst-case bounds on the quality of max-product fixed-points NeurIPS 2010 Approximating MAP by Compensating for Structural Relaxations NeurIPS 2009 Explaining human multiple object tracking as resource-constrained approximate inference in a dynamic probabilistic model NeurIPS 2009 Gaussian process regression with Student-t likelihood NeurIPS 2009 Local Rules for Global MAP: When Do They Work ? NeurIPS 2009 Particle-based Variational Inference for Continuous Systems NeurIPS 2009