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markov chain monte carlo

725 papers

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Also known as

MCMC

Co-occurring keywords

bayesian inference (1907) variational inference (2069) langevin dynamics (128) hamiltonian monte carlo (92) gibbs sampling (201) stochastic gradient (296) mcmc sampling (70) mixing time (70) sampling algorithm (130) gaussian process (1200)

Papers

Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations AISTATS 2018
Learning Descriptor Networks for 3D Shape Synthesis and Analysis CVPR 2018
Stein Variational Gradient Descent Without Gradient ICML 2018
The promises and pitfalls of Stochastic Gradient Langevin Dynamics NIPS 2018
Large-Scale Stochastic Sampling from the Probability Simplex NIPS 2018
Bayesian Approaches to Distribution Regression AISTATS 2018
Bayesian Control of Large MDPs with Unknown Dynamics in Data-Poor Environments NIPS 2018
Minimal I-MAP MCMC for Scalable Structure Discovery in Causal DAG Models ICML 2018
Probabilistic Joint Face-Skull Modelling for Facial Reconstruction CVPR 2018
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC NIPS 2018
Magnetic Hamiltonian Monte Carlo ICML 2017
The Mixing of Markov Chains on Linear Extensions in Practice IJCAI 2017
Nonlinear Maximum Margin Multi-View Learning with Adaptive Kernel IJCAI 2017
Asymptotically exact inference in differentiable generative models AISTATS 2017
Stochastic Gradient Descent as Approximate Bayesian Inference JMLR 2017
Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling JMLR 2017
A Trust-based Mixture of Gaussian Processes Model for Reliable Regression in Participatory Sensing IJCAI 2017
Ensuring Rapid Mixing and Low Bias for Asynchronous Gibbs Sampling IJCAI 2017
A Divergence Bound for Hybrids of MCMC and Variational Inference and an Application to Langevin Dynamics and SGVI ICML 2017
Scalable Bayesian Learning of Recurrent Neural Networks for Language Modeling ACL 2017
PASS-GLM: polynomial approximate sufficient statistics for scalable Bayesian GLM inference NIPS 2017
Polynomial time algorithms for dual volume sampling NIPS 2017
Poisson Random Fields for Dynamic Feature Models JMLR 2017
Bayesian Tensor Regression JMLR 2017
On Markov chain Monte Carlo methods for tall data JMLR 2017