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monte carlo sampling

83 papers

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Also known as

MC SAMPLING MCS

Co-occurring keywords

bayesian inference (1907) monte carlo method (126) variational inference (2069) importance sampling (318) latent variable model (564) variance reduction (523) markov chain monte carlo (725) reinforcement learning (4352) monte carlo (44) stochastic gradient (296)

Papers

Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models ICML 2023
Generative Calibration for In-context Learning EMNLP 2023
Unsupervised Sampling Promoting for Stochastic Human Trajectory Prediction CVPR 2023
Law of Large Numbers for Bayesian two-layer Neural Network trained with Variational Inference COLT 2023
Probabilistic Triangulation for Uncalibrated Multi-View 3D Human Pose Estimation ICCV 2023
Sampling Permutations for Shapley Value Estimation JMLR 2022
Learning General Gaussian Mixture Model with Integral Cosine Similarity IJCAI 2022
Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search CVPR 2022
On Sampling-Based Training Criteria for Neural Language Modeling INTERSPEECH 2021
Kernel Thinning COLT 2021
AutoInt: Automatic Integration for Fast Neural Volume Rendering CVPR 2021
Simpler Certified Radius Maximization by Propagating Covariances CVPR 2021
Mirror Langevin Monte Carlo: the Case Under Isoperimetry NIPS 2021
Fast Bayesian Uncertainty Estimation and Reduction of Batch Normalized Single Image Super-Resolution Network CVPR 2021
Graph reparameterizations for enabling 1000+ Monte Carlo iterations in Bayesian deep neural networks UAI 2021
McFlow: Monte Carlo Flow Models for Data Imputation CVPR 2020
Practical Nonisotropic Monte Carlo Sampling in High Dimensions via Determinantal Point Processes AISTATS 2020
Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks UAI 2020
Amortised Learning by Wake-Sleep ICML 2020
Using Context in Neural Machine Translation Training Objectives ACL 2020
Semi-Supervised Learning for Video Captioning EMNLP 2020
Approximating the Permanent by Sampling from Adaptive Partitions NIPS 2019
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference AISTATS 2019
Improving Quadrature for Constrained Integrands AISTATS 2019
Universal Adversarial Perturbation via Prior Driven Uncertainty Approximation ICCV 2019