monte carlo estimator

StochasticSplats: Stochastic Rasterization for Sorting-Free 3D Gaussian Splatting ICCV 2025 Understanding the difficulties of posterior predictive estimation ICML 2025 Efficient Policy Evaluation with Offline Data Informed Behavior Policy Design ICML 2024 Model-Based Minimum Bayes Risk Decoding for Text Generation ICML 2024 Zeroth-Order Sampling Methods for Non-Log-Concave Distributions: Alleviating Metastability by Denoising Diffusion NeurIPS 2024 A Finite Sample Complexity Bound for Distributionally Robust Q-learning AISTATS 2023 Doubly Robust Stein-Kernelized Monte Carlo Estimator: Simultaneous Bias-Variance Reduction and Supercanonical Convergence JMLR 2023 Meta-learning Control Variates: Variance Reduction with Limited Data UAI 2023 Multiple-policy High-confidence Policy Evaluation AISTATS 2023 Plateau-Reduced Differentiable Path Tracing CVPR 2023 Vector-Valued Control Variates ICML 2023 Robust On-Policy Sampling for Data-Efficient Policy Evaluation in Reinforcement Learning NeurIPS 2022 Statistical, Robustness, and Computational Guarantees for Sliced Wasserstein Distances NeurIPS 2022 A unified view of likelihood ratio and reparameterization gradients AISTATS 2021 Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators JMLR 2020 Adaptive Antithetic Sampling for Variance Reduction ICML 2019 Delayed Sampling and Automatic Rao-Blackwellization of Probabilistic Programs AISTATS 2018 Efficient Gradient-Based Inference through Transformations between Bayes Nets and Neural Nets ICML 2014