approximate inference

Structured Prediction of Network Response ICML 2014 Tilted Variational Bayes AISTATS 2014 Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach ICML 2014 Tree-structured Gaussian Process Approximations NeurIPS 2014 Approximate Bayesian Image Interpretation using Generative Probabilistic Graphics Programs NeurIPS 2013 Approximate Gaussian process inference for the drift function in stochastic differential equations NeurIPS 2013 Approximate Inference in Collective Graphical Models ICML 2013 Approximate Inference in Continuous Determinantal Processes NeurIPS 2013 Approximating the Permanent with Fractional Belief Propagation JMLR 2013 Collapsed Variational Bayesian Inference for Hidden Markov Models AISTATS 2013 Deep Gaussian Processes AISTATS 2013 Demixing odors - fast inference in olfaction NeurIPS 2013 Learning Feature Selection Dependencies in Multi-task Learning NeurIPS 2013 Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets CVPR 2013 Learning to Pass Expectation Propagation Messages NeurIPS 2013 Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization CVPR 2013 Nested Expectation Propagation for Gaussian Process Classification with a Multinomial Probit Likelihood JMLR 2013 On the Complexity and Approximation of Binary Evidence in Lifted Inference NeurIPS 2013 Real-Time Inference for a Gamma Process Model of Neural Spiking NeurIPS 2013 Scaling the Indian Buffet Process via Submodular Maximization ICML 2013 Affine Independent Variational Inference NeurIPS 2012 Approximate Inference by Intersecting Semidefinite Bound and Local Polytope AISTATS 2012 Approximate Inference in Additive Factorial HMMs with Application to Energy Disaggregation AISTATS 2012 Burn-in, bias, and the rationality of anchoring NeurIPS 2012 Complex Inference in Neural Circuits with Probabilistic Population Codes and Topic Models NeurIPS 2012