bayesian inference

1904 papers

Explore in graph

Also known as

MCMC MBR BI BVMM MAP

Co-occurring keywords

variational inference (2069) markov chain monte carlo (724) gaussian process (1198) probabilistic modeling (851) uncertainty quantification (1365) posterior distribution (259) bayesian learning (185) gibbs sampling (201) graphical model (863) probabilistic model (476)

Papers

Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016

Modeling topic dependencies in semantically coherent text spans with copulas COLING 2016

CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data JMLR 2016

String and Membrane Gaussian Processes JMLR 2016

Fast Collocation-Based Bayesian HMM Word Alignment COLING 2016

MCMC Shape Sampling for Image Segmentation With Nonparametric Shape Priors CVPR 2016

Simulation and Calibration of a Fully Bayesian Marked Multidimensional Hawkes Process with Dissimilar Decays ACML 2016

Exploring Topic Discriminating Power of Words in Latent Dirichlet Allocation COLING 2016

Coresets for Scalable Bayesian Logistic Regression NIPS 2016

Stochastic Gradient MCMC with Stale Gradients NIPS 2016

Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NIPS 2016

Operator Variational Inference NIPS 2016

Answer-Type Prediction for Visual Question Answering CVPR 2016

Computational Imaging for VLBI Image Reconstruction CVPR 2016

Mixture of Bilateral-Projection Two-Dimensional Probabilistic Principal Component Analysis CVPR 2016

Cross-Corpora Unsupervised Learning of Trajectories in Autism Spectrum Disorders JMLR 2016

Bayesian Policy Gradient and Actor-Critic Algorithms JMLR 2016

Semiparametric Mean Field Variational Bayes: General Principles and Numerical Issues JMLR 2016

Diversity-Promoting Bayesian Learning of Latent Variable Models ICML 2016

Robust Monte Carlo Sampling using Riemannian Nosé-Poincaré Hamiltonian Dynamics ICML 2016

Variance Reduction in Stochastic Gradient Langevin Dynamics NIPS 2016

Probabilistic Linear Multistep Methods NIPS 2016

An equivalence between high dimensional Bayes optimal inference and M-estimation NIPS 2016

Compressed Gaussian Process for Manifold Regression JMLR 2016

Exploration of the (Non-)Asymptotic Bias and Variance of Stochastic Gradient Langevin Dynamics JMLR 2016