monte carlo estimation

Amortized variance reduction for doubly stochastic objective UAI 2020 Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes ICLR 2019 Data Shapley: Equitable Valuation of Data for Machine Learning ICML 2019 Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019 Divide and Couple: Using Monte Carlo Variational Objectives for Posterior Approximation NeurIPS 2019 Orthogonal Estimation of Wasserstein Distances AISTATS 2019 On Nesting Monte Carlo Estimators ICML 2018 TD or not TD: Analyzing the Role of Temporal Differencing in Deep Reinforcement Learning ICLR 2018 Improving Gibbs Sampler Scan Quality with DoGS ICML 2017 Iterative Refinement of the Approximate Posterior for Directed Belief Networks NeurIPS 2016 Adaptive Monte Carlo via Bandit Allocation ICML 2014 On Measure Concentration of Random Maximum A-Posteriori Perturbations ICML 2014 Improving Policy Gradient Estimates with Influence Information ACML 2011 Monte Carlo Pose Estimation with Quaternion Kernels and the Bingham Distribution RSS 2011 Bootstrapping Apprenticeship Learning NeurIPS 2010 Bayesian Policy Gradient Algorithms NeurIPS 2006 On the Convergence of Optimistic Policy Iteration JMLR 2002