conftrace_

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

Non-Volume Preserving Hamiltonian Monte Carlo and No-U-TurnSamplers AISTATS 2021
A Hybrid Approximation to the Marginal Likelihood AISTATS 2021
Sampling in Combinatorial Spaces with SurVAE Flow Augmented MCMC AISTATS 2021
A Hybrid Stochastic Gradient Hamiltonian Monte Carlo Method AAAI 2021
T-LoHo: A Bayesian Regularization Model for Structured Sparsity and Smoothness on Graphs NIPS 2021
Bayesian time-aligned factor analysis of paired multivariate time series JMLR 2021
Hybrid Message Passing With Performance-Driven Structures for Facial Action Unit Detection CVPR 2021
On the convergence of the Metropolis algorithm with fixed-order updates for multivariate binary probability distributions AISTATS 2021
variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference UAI 2021
Kernel Thinning COLT 2021
No-regret approximate inference via Bayesian optimisation UAI 2021
Learning Cycle-Consistent Cooperative Networks via Alternating MCMC Teaching for Unsupervised Cross-Domain Translation AAAI 2021
Projected Stochastic Gradient Langevin Algorithms for Constrained Sampling and Non-Convex Learning COLT 2021
Adversarial Purification with Score-based Generative Models ICML 2021
An Adaptive-MCMC Scheme for Setting Trajectory Lengths in Hamiltonian Monte Carlo AISTATS 2021
Learning Deep Latent Variable Models by Short-Run MCMC Inference With Optimal Transport Correction CVPR 2021
Rao-Blackwellised parallel MCMC AISTATS 2021
Optimal Quantisation of Probability Measures Using Maximum Mean Discrepancy AISTATS 2021
Entropy-based adaptive Hamiltonian Monte Carlo NIPS 2021
Scaling Hamiltonian Monte Carlo inference for Bayesian neural networks with symmetric splitting UAI 2021
Learning Energy-Based Model with Variational Auto-Encoder as Amortized Sampler AAAI 2021
De-randomizing MCMC dynamics with the diffusion Stein operator NIPS 2021
Language Generation via Combinatorial Constraint Satisfaction: A Tree Search Enhanced Monte-Carlo Approach EMNLP 2020
Hamiltonian Monte Carlo Swindles AISTATS 2020
Variational Learning of Bayesian Neural Networks via Bayesian Dark Knowledge IJCAI 2020