partition function

Belief Propagation: Accurate Marginals or Accurate Partition Function – Where is the Difference? UAI 2019 Energy-Inspired Models: Learning with Sampler-Induced Distributions NeurIPS 2019 Inference and Sampling of K_33-free Ising Models ICML 2019 Interleave Variational Optimization with Monte Carlo Sampling: A Tale of Two Approximate Inference Paradigms AAAI 2019 Spectral Approximate Inference ICML 2019 A Faster Approximation Algorithm for the Gibbs Partition Function COLT 2018 Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net NeurIPS 2018 Bucket Renormalization for Approximate Inference ICML 2018 Compact Representation of Uncertainty in Clustering NeurIPS 2018 Conditional Noise-Contrastive Estimation of Unnormalised Models ICML 2018 Gauged Mini-Bucket Elimination for Approximate Inference AISTATS 2018 A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case AISTATS 2017 Dynamic Importance Sampling for Anytime Bounds of the Partition Function NeurIPS 2017 Efficient Inference for Untied MLNs IJCAI 2017 Gauging Variational Inference NeurIPS 2017 Lost Relatives of the Gumbel Trick ICML 2017 Markov Chain Truncation for Doubly-Intractable Inference AISTATS 2017 Variational Particle Approximations JMLR 2017 Approximate maximum entropy principles via Goemans-Williamson with applications to provable variational methods NeurIPS 2016 Bayesian Generalised Ensemble Markov Chain Monte Carlo AISTATS 2016 Bethe Learning of Graphical Models via MAP Decoding AISTATS 2016 Cooperative Graphical Models NeurIPS 2016 How to calculate partition functions using convex programming hierarchies: provable bounds for variational methods COLT 2016 Partition Functions from Rao-Blackwellized Tempered Sampling ICML 2016 Stochastic Discrete Clenshaw-Curtis Quadrature ICML 2016