marginal likelihood

Learning Gaussian Processes by Minimizing PAC-Bayesian Generalization Bounds NeurIPS 2018 Learning Invariances using the Marginal Likelihood NeurIPS 2018 Marginal Likelihood Training of BiLSTM-CRF for Biomedical Named Entity Recognition from Disjoint Label Sets EMNLP 2018 Noisin: Unbiased Regularization for Recurrent Neural Networks ICML 2018 Variational Rejection Sampling AISTATS 2018 Convolutional Gaussian Processes NeurIPS 2017 End-to-end Neural Coreference Resolution EMNLP 2017 Factorized Asymptotic Bayesian Policy Search for POMDPs IJCAI 2017 Filtering Variational Objectives NeurIPS 2017 Model evidence from nonequilibrium simulations NeurIPS 2017 Perturbative Black Box Variational Inference NeurIPS 2017 An Empirical-Bayes Score for Discrete Bayesian Networks PGM 2016 Bayesian optimization for automated model selection NeurIPS 2016 Early Stopping as Nonparametric Variational Inference AISTATS 2016 PAC-Bayesian Theory Meets Bayesian Inference NeurIPS 2016 Parametric Object Motion From Blur CVPR 2016 Gaussian Process Random Fields NeurIPS 2015 Rebuilding Factorized Information Criterion: Asymptotically Accurate Marginal Likelihood ICML 2015 Asynchronous Anytime Sequential Monte Carlo NeurIPS 2014 Decoupled Variational Gaussian Inference NeurIPS 2014 Estimating Latent-Variable Graphical Models using Moments and Likelihoods ICML 2014 Tilted Variational Bayes AISTATS 2014 A recursive estimate for the predictive likelihood in a topic model AISTATS 2013 Distributed Learning of Gaussian Graphical Models via Marginal Likelihoods AISTATS 2013 Efficient Optimization for Sparse Gaussian Process Regression NeurIPS 2013