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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

Validated Variational Inference via Practical Posterior Error Bounds AISTATS 2020
Black-Box Variational Inference as a Parametric Approximation to Langevin Dynamics ICML 2020
How Good is the Bayes Posterior in Deep Neural Networks Really? ICML 2020
Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev NIPS 2020
Bean Machine: A Declarative Probabilistic Programming Language For Efficient Programmable Inference PGM 2020
Contrastive Divergence Learning with Chained Belief Propagation PGM 2020
Logsmooth Gradient Concentration and Tighter Runtimes for Metropolized Hamiltonian Monte Carlo COLT 2020
Free Energy Wells and Overlap Gap Property in Sparse PCA COLT 2020
Stein Self-Repulsive Dynamics: Benefits From Past Samples NIPS 2020
Exponential ergodicity of mirror-Langevin diffusions NIPS 2020
Joint Stochastic Approximation and Its Application to Learning Discrete Latent Variable Models UAI 2020
Learning Latent Space Energy-Based Prior Model NIPS 2020
Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection ACML 2020
On the Ergodicity, Bias and Asymptotic Normality of Randomized Midpoint Sampling Method NIPS 2020
Marginal Densities, Factor Graph Duality, and High-Temperature Series Expansions AISTATS 2020
Breaking Reversibility Accelerates Langevin Dynamics for Non-Convex Optimization NIPS 2020
Stochastic Stein Discrepancies NIPS 2020
Asymptotically Optimal Exact Minibatch Metropolis-Hastings NIPS 2020
Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond NIPS 2020
Mixed Hamiltonian Monte Carlo for Mixed Discrete and Continuous Variables NIPS 2020
Unsupervised Joint k-node Graph Representations with Compositional Energy-Based Models NIPS 2020
Fast Markov chain Monte Carlo algorithms via Lie groups AISTATS 2020
Stochastic Normalizing Flows NIPS 2020
Hamiltonian Monte Carlo Swindles AISTATS 2020
Likelihood-free MCMC with Amortized Approximate Ratio Estimators ICML 2020