posterior inference

MASSIVE: Tractable and Robust Bayesian Learning of Many-Dimensional Instrumental Variable Models UAI 2020 Neural Clustering Processes ICML 2020 Non Parametric Graph Learning for Bayesian Graph Neural Networks UAI 2020 On Contrastive Learning for Likelihood-free Inference ICML 2020 Posterior Control of Blackbox Generation ACL 2020 Slice Sampling for General Completely Random Measures UAI 2020 Uncertainty in Model-Agnostic Meta-Learning using Variational Inference WACV 2020 A Bayesian Perspective on the Deep Image Prior CVPR 2019 Alleviating Label Switching with Optimal Transport NeurIPS 2019 Analyzing Bayesian Crosslingual Transfer in Topic Models NAACL 2019 A Necessary and Sufficient Stability Notion for Adaptive Generalization NeurIPS 2019 Automated Scalable Bayesian Inference via Hilbert Coresets JMLR 2019 Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification AAAI 2019 Bayesian Relational Memory for Semantic Visual Navigation ICCV 2019 Differentially Private Markov Chain Monte Carlo NeurIPS 2019 Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model NeurIPS 2019 Function Space Particle Optimization for Bayesian Neural Networks ICLR 2019 Gaussian Processes with Linear Operator Inequality Constraints JMLR 2019 Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation NeurIPS 2019 The Variational Predictive Natural Gradient ICML 2019 Thompson Sampling on Symmetric Alpha-Stable Bandits IJCAI 2019 Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent ICML 2018 Bayesian Model-Agnostic Meta-Learning NeurIPS 2018 Covariances, Robustness, and Variational Bayes JMLR 2018 Discretely Relaxing Continuous Variables for tractable Variational Inference NeurIPS 2018