Variational Inference

Variational Inference and Deep Generative Models ACL 2018 Variational Inference based on Robust Divergences AISTATS 2018 Variational Inference with Tail-adaptive f-Divergence NeurIPS 2018 Variational Knowledge Graph Reasoning NAACL 2018 Variational Learning on Aggregate Outputs with Gaussian Processes NeurIPS 2018 Variational Message Passing with Structured Inference Networks ICLR 2018 Variational Network Inference: Strong and Stable with Concrete Support ICML 2018 Variational Rejection Sampling AISTATS 2018 Variational Sequential Monte Carlo AISTATS 2018 Wasserstein Variational Inference NeurIPS 2018 A Conditional Variational Framework for Dialog Generation ACL 2017 A Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering NeurIPS 2017 A Generative Parser with a Discriminative Recognition Algorithm ACL 2017 A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings ACML 2017 A-NICE-MC: Adversarial Training for MCMC NeurIPS 2017 A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation JMLR 2017 Averaged Collapsed Variational Bayes Inference JMLR 2017 Concrete Dropout NeurIPS 2017 Conjugate-Computation Variational Inference : Converting Variational Inference in Non-Conjugate Models to Inferences in Conjugate Models AISTATS 2017 Context Selection for Embedding Models NeurIPS 2017 Dense Distributions from Sparse Samples: Improved Gibbs Sampling Parameter Estimators for LDA JMLR 2017 Differentiable Learning of Submodular Models NeurIPS 2017 Doubly Stochastic Variational Inference for Deep Gaussian Processes NeurIPS 2017 Dynamic Programming Bipartite Belief Propagation For Hyper Graph Matching IJCAI 2017 Efficient and Flexible Inference for Stochastic Systems NeurIPS 2017