importance sampling

Optimization and Bayes: A Trade-off for Overparameterized Neural Networks NeurIPS 2023 PA&DA: Jointly Sampling Path and Data for Consistent NAS CVPR 2023 Piecewise Deterministic Markov Processes for Bayesian Neural Networks UAI 2023 Policy-Adaptive Estimator Selection for Off-Policy Evaluation AAAI 2023 Probabilistic Querying of Continuous-Time Event Sequences AISTATS 2023 Provable benefits of annealing for estimating normalizing constants: Importance Sampling, Noise-Contrastive Estimation, and beyond NeurIPS 2023 Refined Regret for Adversarial MDPs with Linear Function Approximation ICML 2023 RL-based Stateful Neural Adaptive Sampling and Denoising for Real-Time Path Tracing NeurIPS 2023 Scaling Marginalized Importance Sampling to High-Dimensional State-Spaces via State Abstraction AAAI 2023 SE(3) Equivariant Augmented Coupling Flows NeurIPS 2023 Should you marginalize over possible tokenizations? ACL 2023 SMCP3: Sequential Monte Carlo with Probabilistic Program Proposals AISTATS 2023 Stein Π-Importance Sampling NeurIPS 2023 Supported Value Regularization for Offline Reinforcement Learning NeurIPS 2023 The Sample Complexity of Approximate Rejection Sampling With Applications to Smoothed Online Learning COLT 2023 Toward Fairness in Text Generation via Mutual Information Minimization based on Importance Sampling AISTATS 2023 Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning ICML 2023 Truncating Trajectories in Monte Carlo Reinforcement Learning ICML 2023 VLIS: Unimodal Language Models Guide Multimodal Language Generation EMNLP 2023 Adaptive Importance Sampling meets Mirror Descent : a Bias-variance Tradeoff AISTATS 2022 Algorithms for the Communication of Samples ICML 2022 A Minimax Learning Approach to Off-Policy Evaluation in Confounded Partially Observable Markov Decision Processes ICML 2022 Amortized Rejection Sampling in Universal Probabilistic Programming AISTATS 2022 Blockwise Sequential Model Learning for Partially Observable Reinforcement Learning AAAI 2022 Cache-Augmented Inbatch Importance Resampling for Training Recommender Retriever NeurIPS 2022