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Bayesian Inference

4821 directly classified papers

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Papers

The Generalized Reparameterization Gradient NIPS 2016
Improved Variational Inference with Inverse Autoregressive Flow NIPS 2016
A Variational Analysis of Stochastic Gradient Algorithms ICML 2016
Operator Variational Inference NIPS 2016
DISCO Nets : DISsimilarity COefficients Networks NIPS 2016
Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NIPS 2016
Stochastic Gradient MCMC with Stale Gradients NIPS 2016
Diversity-Promoting Bayesian Learning of Latent Variable Models ICML 2016
Threshold Learning for Optimal Decision Making NIPS 2016
The Forget-me-not Process NIPS 2016
Parameter Learning for Log-supermodular Distributions NIPS 2016
Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation NIPS 2016
Sampling for Bayesian Program Learning NIPS 2016
Variance Reduction in Stochastic Gradient Langevin Dynamics NIPS 2016
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling NIPS 2016
Bayesian optimization for automated model selection NIPS 2016
Bayesian Optimization for Probabilistic Programs NIPS 2016
Probabilistic Linear Multistep Methods NIPS 2016
Higher-Order Inference for Multi-Class Log-Supermodular Models ICCV 2015
Learning The Structure of Deep Convolutional Networks ICCV 2015
Scalable Nonparametric Multiway Data Analysis AISTATS 2015
Particle Gibbs for Bayesian Additive Regression Trees AISTATS 2015
Consensus Message Passing for Layered Graphical Models AISTATS 2015
Exact Bayesian Learning of Ancestor Relations in Bayesian Networks AISTATS 2015
Video Anomaly Detection and Localization Using Hierarchical Feature Representation and Gaussian Process Regression CVPR 2015