Variational Inference

Variational Training for Large-Scale Noisy-OR Bayesian Networks UAI 2019 A Discriminative Latent-Variable Model for Bilingual Lexicon Induction EMNLP 2018 A Stochastic Decoder for Neural Machine Translation ACL 2018 A Structured Variational Autoencoder for Contextual Morphological Inflection ACL 2018 Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language NeurIPS 2018 Bayesian Alignments of Warped Multi-Output Gaussian Processes NeurIPS 2018 Bayesian Model-Agnostic Meta-Learning NeurIPS 2018 Boosting Variational Inference: an Optimization Perspective AISTATS 2018 Bucket Renormalization for Approximate Inference ICML 2018 Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means AISTATS 2018 Cluster Variational Approximations for Structure Learning of Continuous-Time Bayesian Networks from Incomplete Data NeurIPS 2018 Compressing Neural Networks using the Variational Information Bottleneck ICML 2018 Conditional Word Embedding and Hypothesis Testing via Bayes-by-Backprop EMNLP 2018 Deep Generative Models with Learnable Knowledge Constraints NeurIPS 2018 Estimation of the Number of Speakers with Variational Bayesian PLDA in the DIHARD Diarization Challenge. Interspeech 2018 Fast Variational Bayes for Heavy-tailed PLDA Applied to i-vectors and x-vectors Interspeech 2018 Feature-correlation-aware Gaussian Process Latent Variable Model ACML 2018 Fixing a Broken ELBO ICML 2018 Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery Interspeech 2018 Hamiltonian Variational Auto-Encoder NeurIPS 2018 Heterogeneous Multi-output Gaussian Process Prediction NeurIPS 2018 Importance Weighting and Variational Inference NeurIPS 2018 Large-Scale Cox Process Inference using Variational Fourier Features ICML 2018 Large-Scale Stochastic Sampling from the Probability Simplex NeurIPS 2018 Mean Field for the Stochastic Blockmodel: Optimization Landscape and Convergence Issues NeurIPS 2018