monte carlo sampling

Kernel Thinning COLT 2021 Mirror Langevin Monte Carlo: the Case Under Isoperimetry NeurIPS 2021 On Sampling-Based Training Criteria for Neural Language Modeling Interspeech 2021 Simpler Certified Radius Maximization by Propagating Covariances CVPR 2021 Amortised Learning by Wake-Sleep ICML 2020 Flexible Approximate Inference via Stratified Normalizing Flows UAI 2020 Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks UAI 2020 McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020 Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020 Semi-Supervised Learning for Video Captioning EMNLP 2020 Using Context in Neural Machine Translation Training Objectives ACL 2020 Approximating the Permanent by Sampling from Adaptive Partitions NeurIPS 2019 CECL at SemEval-2019 Task 3: Using Surface Learning for Detecting Emotion in Textual Conversations SemEval 2019 Convolutional Gaussian Embeddings for Personalized Recommendation with Uncertainty IJCAI 2019 Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019 Improving Quadrature for Constrained Integrands AISTATS 2019 Inherent Weight Normalization in Stochastic Neural Networks NeurIPS 2019 Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms AAAI 2019 Policy Optimization with Model-Based Explorations AAAI 2019 Unifying Orthogonal Monte Carlo Methods ICML 2019 Universal Adversarial Perturbation via Prior Driven Uncertainty Approximation ICCV 2019 Variance Reduction in Monte Carlo Counterfactual Regret Minimization (VR-MCCFR) for Extensive Form Games Using Baselines AAAI 2019 Geometrically Coupled Monte Carlo Sampling NeurIPS 2018 Langevin Monte Carlo and JKO splitting COLT 2018 Monte Carlo Syntax Marginals for Exploring and Using Dependency Parses NAACL 2018