Bayesian Inference

Expectation Propagation for t-Exponential Family Using q-Algebra NeurIPS 2017 Exploiting Causality for Selective Belief Filtering in Dynamic Bayesian Networks (Extended Abstract) IJCAI 2017 Extending Model-based Policy Gradients for Robots in Heteroscedastic Environments CoRL 2017 Factorized Asymptotic Bayesian Policy Search for POMDPs IJCAI 2017 Fast Bayesian Intensity Estimation for the Permanental Process ICML 2017 Fast Bayesian Optimization of Machine Learning Hyperparameters on Large Datasets AISTATS 2017 Fast Black-box Variational Inference through Stochastic Trust-Region Optimization NeurIPS 2017 Fast Fourier Color Constancy CVPR 2017 Fast Sparse Gaussian Markov Random Fields Learning Based on Cholesky Factorization IJCAI 2017 Filtering Variational Objectives NeurIPS 2017 Fractional Langevin Monte Carlo: Exploring Levy Driven Stochastic Differential Equations for Markov Chain Monte Carlo ICML 2017 From Bayesian Sparsity to Gated Recurrent Nets NeurIPS 2017 From Patches to Images: A Nonparametric Generative Model ICML 2017 Gain Compensation for Fast i-Vector Extraction Over Short Duration Interspeech 2017 Gaussian process based nonlinear latent structure discovery in multivariate spike train data NeurIPS 2017 Generalized Pólya Urn for Time-Varying Pitman-Yor Processes JMLR 2017 GibbsNet: Iterative Adversarial Inference for Deep Graphical Models NeurIPS 2017 GPflow: A Gaussian Process Library using TensorFlow JMLR 2017 Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery Interspeech 2017 Hierarchical Constrained Bayesian Optimization for Feature, Acoustic Model and Decoder Parameter Optimization Interspeech 2017 Hierarchical Implicit Models and Likelihood-Free Variational Inference NeurIPS 2017 Hierarchically-partitioned Gaussian Process Approximation AISTATS 2017 High Dimensional Bayesian Optimization using Dropout IJCAI 2017 High Dimensional Bayesian Optimization with Elastic Gaussian Process ICML 2017 Identification of Gaussian Process State Space Models NeurIPS 2017