bayesian inference

Variance Reduction in Stochastic Gradient Langevin Dynamics NeurIPS 2016 Variational Gaussian Copula Inference AISTATS 2016 A Bayesian Framework for Modeling Confidence in Perceptual Decision Making NeurIPS 2015 A Bayesian nonparametric procedure for comparing algorithms ICML 2015 A Complete Recipe for Stochastic Gradient MCMC NeurIPS 2015 A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multi-Resolution Structure NeurIPS 2015 A Gaussian Process Model of Quasar Spectral Energy Distributions NeurIPS 2015 A Probabilistic Model for Dirty Multi-task Feature Selection ICML 2015 Asymmetric Transfer Learning with Deep Gaussian Processes ICML 2015 Automatic Variational Inference in Stan NeurIPS 2015 Bayesian Adaptive Matrix Factorization With Automatic Model Selection CVPR 2015 Bayesian dark knowledge NeurIPS 2015 Bayesian Inference for Neighborhood Filters With Application in Denoising CVPR 2015 Bayesian Manifold Learning: The Locally Linear Latent Variable Model (LL-LVM) NeurIPS 2015 Bayesian Multiple Target Localization ICML 2015 Bidirectional Recurrent Neural Networks as Generative Models NeurIPS 2015 Biologically Inspired Dynamic Textures for Probing Motion Perception NeurIPS 2015 Bounding errors of Expectation-Propagation NeurIPS 2015 Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields AISTATS 2015 Celeste: Variational inference for a generative model of astronomical images ICML 2015 Controversy in mechanistic modelling with Gaussian processes ICML 2015 Convergence rate of Bayesian tensor estimator and its minimax optimality ICML 2015 Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling NeurIPS 2015 Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation NeurIPS 2015 Enabling scalable stochastic gradient-based inference for Gaussian processes by employing the Unbiased LInear System SolvEr (ULISSE) ICML 2015