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Bayesian Inference

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Papers

Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments ICML 2019
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces ICML 2019
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing ICML 2019
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations ICML 2019
Understanding and Accelerating Particle-Based Variational Inference ICML 2019
Understanding MCMC Dynamics as Flows on the Wasserstein Space ICML 2019
Bayesian Counterfactual Risk Minimization ICML 2019
Generalized Approximate Survey Propagation for High-Dimensional Estimation ICML 2019
Variational Implicit Processes ICML 2019
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE ICML 2019
Bayesian leave-one-out cross-validation for large data ICML 2019
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models ICML 2019
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems ICML 2019
Dropout as a Structured Shrinkage Prior ICML 2019
Hybrid Models with Deep and Invertible Features ICML 2019
A Framework for Bayesian Optimization in Embedded Subspaces ICML 2019
Tensor Variable Elimination for Plated Factor Graphs ICML 2019
Nonparametric Bayesian Deep Networks with Local Competition ICML 2019
Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation ICML 2019
Efficient learning of smooth probability functions from Bernoulli tests with guarantees ICML 2019
Good Initializations of Variational Bayes for Deep Models ICML 2019
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples ICML 2019
A Contrastive Divergence for Combining Variational Inference and MCMC ICML 2019
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference ICML 2019
Deep Gaussian Processes with Importance-Weighted Variational Inference ICML 2019