conftrace_
← Models
Deep Learning › Models ›

Variational Inference

1,952 papers

Papers per year

2
9
31
252
103
'05
'10
'15
'20
'25

Papers

Generating Relevant and Coherent Dialogue Responses using Self-Separated Conditional Variational AutoEncoders ACL 2021
Unsupervised Cross-Domain Prerequisite Chain Learning using Variational Graph Autoencoders ACL 2021
Unsupervised Class-Specific Abstractive Summarization of Customer Reviews ACL 2021
Learning Sparse Sentence Encoding without Supervision: An Exploration of Sparsity in Variational Autoencoders ACL 2021
Improving Gaussian mixture latent variable model convergence with Optimal Transport ACML 2021
DAGSurv: Directed Ayclic Graph Based Survival Analysis Using Deep Neural Networks ACML 2021
Cross-structural Factor-topic Model: Document Analysis with Sophisticated Covariates ACML 2021
Multi-stream based marked point process ACML 2021
Automatic structured variational inference AISTATS 2021
Improving predictions of Bayesian neural nets via local linearization AISTATS 2021
Moment-Based Variational Inference for Stochastic Differential Equations AISTATS 2021
A Variational Inference Approach to Learning Multivariate Wold Processes AISTATS 2021
Variational Selective Autoencoder: Learning from Partially-Observed Heterogeneous Data AISTATS 2021
Statistical Guarantees for Transformation Based Models with applications to Implicit Variational Inference AISTATS 2021
Variational inference for nonlinear ordinary differential equations AISTATS 2021
Automatic Differentiation Variational Inference with Mixtures AISTATS 2021
Hyperbolic graph embedding with enhanced semi-implicit variational inference. AISTATS 2021
Scalable Gaussian Process Variational Autoencoders AISTATS 2021
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders AISTATS 2021
Latent Gaussian process with composite likelihoods and numerical quadrature AISTATS 2021
Deep Generative Missingness Pattern-Set Mixture Models AISTATS 2021
A Scalable Gradient Free Method for Bayesian Experimental Design with Implicit Models AISTATS 2021
Rate-Regularization and Generalization in Variational Autoencoders AISTATS 2021
On Multilevel Monte Carlo Unbiased Gradient Estimation for Deep Latent Variable Models AISTATS 2021
Meta-Learning Divergences for Variational Inference AISTATS 2021