approximate inference

Efficient Sampling for Bipartite Matching Problems NeurIPS 2012 Expectation Propagation in Gaussian Process Dynamical Systems NeurIPS 2012 Hierarchical Motion Planning in Topological Representations RSS 2012 Learning visual motion in recurrent neural networks NeurIPS 2012 Near-Optimal MAP Inference for Determinantal Point Processes NeurIPS 2012 Nonparanormal Belief Propagation (NPNBP) NeurIPS 2012 On Stochastic Optimal Control and Reinforcement Learning by Approximate Inference RSS 2012 On Triangular versus Edge Representations --- Towards Scalable Modeling of Networks NeurIPS 2012 A Bayesian Approximation Method for Online Ranking JMLR 2011 A conditional game for comparing approximations AISTATS 2011 An Application of Tree-Structured Expectation Propagation for Channel Decoding NeurIPS 2011 Approximate inference for the loss-calibrated Bayesian AISTATS 2011 Approximate Marginals in Latent Gaussian Models JMLR 2011 Convergent Decomposition Solvers for Tree-reweighted Free Energies AISTATS 2011 Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials NeurIPS 2011 Empirical Risk Minimization of Graphical Model Parameters Given Approximate Inference, Decoding, and Model Structure AISTATS 2011 Fast Convergent Algorithms for Expectation Propagation Approximate Bayesian Inference AISTATS 2011 Faster Algorithms for Max-Product Message-Passing JMLR 2011 Learning unbelievable probabilities NeurIPS 2011 Neuronal Adaptation for Sampling-Based Probabilistic Inference in Perceptual Bistability NeurIPS 2011 Robust Gaussian Process Regression with a Student- Likelihood JMLR 2011 Robust Multi-Class Gaussian Process Classification NeurIPS 2011 Select and Sample - A Model of Efficient Neural Inference and Learning NeurIPS 2011 Sparse Bayesian Multi-Task Learning NeurIPS 2011 Switch-Reset Models : Exact and Approximate Inference AISTATS 2011