contrastive divergence

Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016 Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models ACML 2015 Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy NeurIPS 2015 Unsupervised Riemannian Metric Learning for Histograms Using Aitchison Transformations ICML 2015 Improved Multimodal Deep Learning with Variation of Information NeurIPS 2014 Interpretable Sparse High-Order Boltzmann Machines AISTATS 2014 Learning Heterogeneous Hidden Markov Random Fields AISTATS 2014 Training Energy-Based Models for Time-Series Imputation JMLR 2013 Unifying Non-Maximum Likelihood Learning Objectives with Minimum KL Contraction NeurIPS 2011 Inductive Principles for Restricted Boltzmann Machine Learning AISTATS 2010 Learning with Blocks: Composite Likelihood and Contrastive Divergence AISTATS 2010 On the Convergence Properties of Contrastive Divergence AISTATS 2010 Implicit Mixtures of Restricted Boltzmann Machines NeurIPS 2008 Energy-Based Models for Sparse Overcomplete Representations JMLR 2003