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Bayesian Inference

5,566 papers

Papers per year

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100
176
522
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Papers

Bayesian Multiple Target Localization ICML 2015
A Hybrid Approach for Probabilistic Inference using Random Projections ICML 2015
Scalable Bayesian Optimization Using Deep Neural Networks ICML 2015
A Fast Variational Approach for Learning Markov Random Field Language Models ICML 2015
Distributed Inference for Dirichlet Process Mixture Models ICML 2015
Scaling up Natural Gradient by Sparsely Factorizing the Inverse Fisher Matrix ICML 2015
A Convex Exemplar-based Approach to MAD-Bayes Dirichlet Process Mixture Models ICML 2015
Privacy for Free: Posterior Sampling and Stochastic Gradient Monte Carlo ICML 2015
A trust-region method for stochastic variational inference with applications to streaming data ICML 2015
Inference in a Partially Observed Queuing Model with Applications in Ecology ICML 2015
Pushing Forward Marginal MAP with Best-First Search IJCAI 2015
Statistical Decision Making for Optimal Budget Allocation in Crowd Labeling JMLR 2015
Risk Bounds for the Majority Vote: From a PAC-Bayesian Analysis to a Learning Algorithm JMLR 2015
Bayesian Nonparametric Crowdsourcing JMLR 2015
Concave Penalized Estimation of Sparse Gaussian Bayesian Networks JMLR 2015
The Libra Toolkit for Probabilistic Models JMLR 2015
Bayesian Nonparametric Covariance Regression JMLR 2015
pyGPs -- A Python Library for Gaussian Process Regression and Classification JMLR 2015
Decision Boundary for Discrete Bayesian Network Classifiers JMLR 2015
Optimal Bayesian Estimation in Random Covariate Design with a Rescaled Gaussian Process Prior JMLR 2015
Optimality of Poisson Processes Intensity Learning with Gaussian Processes JMLR 2015
IMU Preintegration on Manifold for Efficient Visual-Inertial Maximum-a-Posteriori Estimation RSS 2015
Probabilistic Semi-Dense Mapping from Highly Accurate Feature-Based Monocular SLAM RSS 2015
Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling NIPS 2014
Gaussian Process Volatility Model NIPS 2014