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Variational Inference

767 directly classified papers

Papers per year

Papers

Speaker Clustering by Iteratively Finding Discriminative Feature Space and Cluster Labels INTERSPEECH 2017
Stochastic Gradient MCMC Methods for Hidden Markov Models ICML 2017
Variational Policy for Guiding Point Processes ICML 2017
Latent Variable Dialogue Models and their Diversity EACL 2017
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017
Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery INTERSPEECH 2017
Averaged Collapsed Variational Bayes Inference JMLR 2017
A Conditional Variational Framework for Dialog Generation ACL 2017
Improving Variational Methods via Pairwise Linear Response Identities JMLR 2017
Statistical Inference with Unnormalized Discrete Models and Localized Homogeneous Divergences JMLR 2017
Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA JMLR 2017
A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation JMLR 2017
Identification of Gaussian Process State Space Models NIPS 2017
Stein Variational Gradient Descent as Gradient Flow NIPS 2017
Differentiable Learning of Submodular Models NIPS 2017
A-NICE-MC: Adversarial Training for MCMC NIPS 2017
f-GANs in an Information Geometric Nutshell NIPS 2017
Reducing Reparameterization Gradient Variance NIPS 2017
Variational Inference via $\chi$ Upper Bound Minimization NIPS 2017
VAE Learning via Stein Variational Gradient Descent NIPS 2017
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders NIPS 2017
Hierarchical Implicit Models and Likelihood-Free Variational Inference NIPS 2017
Context Selection for Embedding Models NIPS 2017
Excess Risk Bounds for the Bayes Risk using Variational Inference in Latent Gaussian Models NIPS 2017
Doubly Stochastic Variational Inference for Deep Gaussian Processes NIPS 2017