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Bayesian Inference

4821 directly classified papers

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Papers

Scan Order in Gibbs Sampling: Models in Which it Matters and Bounds on How Much NIPS 2016
Provable Bayesian Inference via Particle Mirror Descent AISTATS 2016
Bayesian Optimization with Robust Bayesian Neural Networks NIPS 2016
VIME: Variational Information Maximizing Exploration NIPS 2016
Unifying Count-Based Exploration and Intrinsic Motivation NIPS 2016
A Bayesian Nonparametric Approach for Estimating Individualized Treatment-Response Curves MLHC 2016
Variational Information Maximization for Feature Selection NIPS 2016
Scalable geometric density estimation AISTATS 2016
Improving Boundary Estimation in Audiovisual Speech Activity Detection Using Bayesian Information Criterion INTERSPEECH 2016
Bayesian Nonparametric Kernel-Learning AISTATS 2016
Adapting Multicomponent Predictive Systems using Hybrid Adaptation Strategies with Auto-WEKA in Process Industry AUTOML 2016
Stochastic Gradient Richardson-Romberg Markov Chain Monte Carlo NIPS 2016
Optimization as Estimation with Gaussian Processes in Bandit Settings AISTATS 2016
Probing the Compositionality of Intuitive Functions NIPS 2016
Bayesian optimization for automated model selection AUTOML 2016
Early Stopping as Nonparametric Variational Inference AISTATS 2016
Exponential Stochastic Cellular Automata for Massively Parallel Inference AISTATS 2016
Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016
Stochastic Variational Inference for the HDP-HMM AISTATS 2016
Scalable MCMC for Mixed Membership Stochastic Blockmodels AISTATS 2016
Variational Tempering AISTATS 2016
K2-ABC: Approximate Bayesian Computation with Kernel Embeddings AISTATS 2016
Latent Point Process Allocation AISTATS 2016
On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes AISTATS 2016
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models AISTATS 2016