latent gaussian model

Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models ICML 2023 Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond NeurIPS 2020 Infinite ShapeOdds: Nonparametric Bayesian Models for Shape Representations AAAI 2020 Icebreaker: Element-wise Efficient Information Acquisition with a Bayesian Deep Latent Gaussian Model NeurIPS 2019 Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NeurIPS 2017 Learning Deep Latent Gaussian Models with Markov Chain Monte Carlo ICML 2017 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 Dependent Multinomial Models Made Easy: Stick-Breaking with the Polya-gamma Augmentation NeurIPS 2015 Latent Gaussian Models for Topic Modeling AISTATS 2014 Fast Dual Variational Inference for Non-Conjugate Latent Gaussian Models ICML 2013 A Stick-Breaking Likelihood for Categorical Data Analysis with Latent Gaussian Models AISTATS 2012 Approximate Marginals in Latent Gaussian Models JMLR 2011 Improving posterior marginal approximations in latent Gaussian models AISTATS 2010 Slice sampling covariance hyperparameters of latent Gaussian models NeurIPS 2010