posterior distribution

Recursive Monte Carlo and variational inference with auxiliary variables UAI 2022 The Effects of Invertibility on the Representational Complexity of Encoders in Variational Autoencoders ICLR 2022 Towards Multimodal Depth Estimation From Light Fields CVPR 2022 Transmission-Guided Bayesian Generative Model for Smoke Segmentation AAAI 2022 Truncated proposals for scalable and hassle-free simulation-based inference NeurIPS 2022 Variational Inference in high-dimensional linear regression JMLR 2022 Variational methods for simulation-based inference ICLR 2022 Wide Mean-Field Bayesian Neural Networks Ignore the Data AISTATS 2022 A Bayesian Approach for Subset Selection in Contextual Bandits AAAI 2021 ASR Posterior-Based Loss for Multi-Task End-to-End Speech Translation Interspeech 2021 Conformal Bayesian Computation NeurIPS 2021 Consistency of Gaussian Process Regression in Metric Spaces JMLR 2021 Deep Probabilistic Imaging: Uncertainty Quantification and Multi-modal Solution Characterization for Computational Imaging AAAI 2021 Efficient sampling from the Bingham distribution ALT 2021 Fairness in Ranking under Uncertainty NeurIPS 2021 GemBag: Group Estimation of Multiple Bayesian Graphical Models JMLR 2021 Generative Particle Variational Inference via Estimation of Functional Gradients ICML 2021 Geometric convergence of elliptical slice sampling ICML 2021 HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference AAAI 2021 How Tight Can PAC-Bayes be in the Small Data Regime? NeurIPS 2021 Learning to Ground Visual Objects for Visual Dialog EMNLP 2021 Neural Posterior Domain Randomization CoRL 2021 Neural Thompson Sampling ICLR 2021 On the Convergence of Hamiltonian Monte Carlo with Stochastic Gradients ICML 2021 On the Role of Data in PAC-Bayes Bounds AISTATS 2021