hierarchical prior

ARD-VAE: A Statistical Formulation to Find the Relevant Latent Dimensions of Variational Autoencoders WACV 2025 RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations ICLR 2024 Posterior Consistency for Bayesian Relevance Vector Machines JMLR 2023 Collapsed Variational Bounds for Bayesian Neural Networks NeurIPS 2021 Hierarchical Indian buffet neural networks for Bayesian continual learning UAI 2021 Sparse within Sparse Gaussian Processes using Neighbor Information ICML 2021 Bayesian Hierarchical Words Representation Learning ACL 2020 Hierarchical Gaussian Process Priors for Bayesian Neural Network Weights NeurIPS 2020 Learning Hierarchical Priors in VAEs NeurIPS 2019 Variational Bayesian Dropout With a Hierarchical Prior CVPR 2019 Joint Autoregressive and Hierarchical Priors for Learned Image Compression NeurIPS 2018 VAE with a VampPrior AISTATS 2018 Bayesian Models of Data Streams with Hierarchical Power Priors ICML 2017 Observational-Interventional Priors for Dose-Response Learning NeurIPS 2016 Risk and Regret of Hierarchical Bayesian Learners ICML 2015 Expectation Propagation for Neural Networks with Sparsity-Promoting Priors JMLR 2014 Sparse Bayesian structure learning with “dependent relevance determination” priors NeurIPS 2014 Adaptive Sparsity in Gaussian Graphical Models ICML 2013 Bayesian active learning with localized priors for fast receptive field characterization NeurIPS 2012 Bayesian models for Large-scale Hierarchical Classification NeurIPS 2012