prior distribution

Probing BERT’s priors with serial reproduction chains ACL 2022 Transformers Can Do Bayesian Inference ICLR 2022 A Contrastive Learning Approach for Training Variational Autoencoder Priors NeurIPS 2021 Bayesian neural network unit priors and generalized Weibull-tail property ACML 2021 BooVAE: Boosting Approach for Continual Learning of VAE NeurIPS 2021 How Tight Can PAC-Bayes be in the Small Data Regime? NeurIPS 2021 Learning to Ground Visual Objects for Visual Dialog EMNLP 2021 On the Role of Data in PAC-Bayes Bounds AISTATS 2021 The Ridgelet Prior: A Covariance Function Approach to Prior Specification for Bayesian Neural Networks JMLR 2021 Variational Autoencoder with Learned Latent Structure AISTATS 2021 Flexible Prior Elicitation via the Prior Predictive Distribution UAI 2020 Meta-Learning PAC-Bayes Priors in Model Averaging AAAI 2020 PoRB-Nets: Poisson Process Radial Basis Function Networks UAI 2020 Towards a Better Understanding of Label Smoothing in Neural Machine Translation AACL 2020 Variational Autoencoders with Riemannian Brownian Motion Priors ICML 2020 A Prior of a Googol Gaussians: a Tensor Ring Induced Prior for Generative Models NeurIPS 2019 Learning to Select Knowledge for Response Generation in Dialog Systems IJCAI 2019 Resampled Priors for Variational Autoencoders AISTATS 2019 Towards Zero-shot Language Modeling EMNLP 2019 Variational Autoencoder with Implicit Optimal Priors AAAI 2019 Word Embedding as Maximum A Posteriori Estimation AAAI 2019 Data-dependent PAC-Bayes priors via differential privacy NeurIPS 2018 Don't Just Assume; Look and Answer: Overcoming Priors for Visual Question Answering CVPR 2018 Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory ICML 2018 Stochastic Video Generation with a Learned Prior ICML 2018