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Bayesian Learning

1,663 papers

Papers per year

2
48
52
137
36
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Papers

Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) ICML 2015
Exponential Integration for Hamiltonian Monte Carlo ICML 2015
Manifold-valued Dirichlet Processes ICML 2015
Non-Gaussian Discriminative Factor Models via the Max-Margin Rank-Likelihood ICML 2015
Metadata Dependent Mondrian Processes ICML 2015
Controversy in mechanistic modelling with Gaussian processes ICML 2015
An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process ICML 2015
Weight Uncertainty in Neural Network ICML 2015
Large-scale Distributed Dependent Nonparametric Trees ICML 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks ICML 2015
Bayesian Multiple Target Localization ICML 2015
Distributed Inference for 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
Bayesian Nonparametric Crowdsourcing JMLR 2015
Concave Penalized Estimation of Sparse Gaussian Bayesian Networks JMLR 2015
Bayesian Nonparametric Covariance Regression JMLR 2015
A New Perspective and Extension of the Gaussian Filter RSS 2015
Spatio-temporal Representations of Uncertainty in Spiking Neural Networks NIPS 2014
Beta-Negative Binomial Process and Exchangeable Random Partitions for Mixed-Membership Modeling NIPS 2014
Gaussian Process Volatility Model NIPS 2014
Dependent nonparametric trees for dynamic hierarchical clustering NIPS 2014
Distance-Based Network Recovery under Feature Correlation NIPS 2014
A Framework for Testing Identifiability of Bayesian Models of Perception NIPS 2014
Spectral Methods for Indian Buffet Process Inference NIPS 2014