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bayesian inference

1904 papers

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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

Stochastic Gradient Hamiltonian Monte Carlo ICML 2014
A Bayesian Framework For the Local Configuration of Retinal Junctions CVPR 2014
Kernel Adaptive Metropolis-Hastings ICML 2014
Latent Gaussian Models for Topic Modeling AISTATS 2014
Lower Bounds for the Gibbs Sampler over Mixtures of Gaussians ICML 2014
The Dependent Dirichlet Process Mixture of Objects for Detection-free Tracking and Object Modeling AISTATS 2014
Improving Prediction from Dirichlet Process Mixtures via Enrichment JMLR 2014
Gaussian Process Classification and Active Learning with Multiple Annotators ICML 2014
Online Bayesian Passive-Aggressive Learning ICML 2014
A Bayesian Framework for Online Classifier Ensemble ICML 2014
Bayesian Active Contours with Affine-Invariant, Elastic Shape Prior CVPR 2014
Learning Modular Structures from Network Data and Node Variables ICML 2014
Probabilistic ODE Solvers with Runge-Kutta Means NIPS 2014
Agnostic Bayesian Learning of Ensembles ICML 2014
Variational Gaussian Inference for Bilinear Models of Count Data ACML 2014
Bayesian View Synthesis and Image-Based Rendering Principles CVPR 2014
Spherical Hamiltonian Monte Carlo for Constrained Target Distributions ICML 2014
Non-Parametric Bayesian Constrained Local Models CVPR 2014
Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations ICML 2014
Doubly Stochastic Variational Bayes for non-Conjugate Inference ICML 2014
Stochastic Variational Inference for Bayesian Time Series Models ICML 2014
From MAP to Marginals: Variational Inference in Bayesian Submodular Models NIPS 2014
Hardness of parameter estimation in graphical models NIPS 2014
On Prior Distributions and Approximate Inference for Structured Variables NIPS 2014
Semi-supervised Learning with Deep Generative Models NIPS 2014