approximate posterior

Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors AAAI 2025 Langevin Thompson Sampling with Logarithmic Communication: Bandits and Reinforcement Learning ICML 2023 Riemannian Laplace approximations for Bayesian neural networks NeurIPS 2023 Variational Distribution Learning for Unsupervised Text-to-Image Generation CVPR 2023 Latent Time Neural Ordinary Differential Equations AAAI 2022 Global inducing point variational posteriors for Bayesian neural networks and deep Gaussian processes ICML 2021 Undirected Graphical Models as Approximate Posteriors ICML 2020 Variational Neural Machine Translation with Normalizing Flows ACL 2020 Iterative Amortized Inference ICML 2018 Doubly Stochastic Variational Inference for Deep Gaussian Processes NeurIPS 2017 Early Stopping as Nonparametric Variational Inference AISTATS 2016 Iterative Refinement of the Approximate Posterior for Directed Belief Networks NeurIPS 2016 Variational Inference with Normalizing Flows ICML 2015 Latent Data Association: Bayesian Model Selection for Multi-target Tracking ICCV 2013