Variational Inference

Doubly Stochastic Variational Inference for Deep Gaussian Processes NeurIPS 2017 Dropout Inference in Bayesian Neural Networks with Alpha-divergences ICML 2017 Factorized Variational Autoencoders for Modeling Audience Reactions to Movies CVPR 2017 Fast amortized inference of neural activity from calcium imaging data with variational autoencoders NeurIPS 2017 Fast Black-box Variational Inference through Stochastic Trust-Region Optimization NeurIPS 2017 Filtering Variational Objectives NeurIPS 2017 G2DeNet: Global Gaussian Distribution Embedding Network and Its Application to Visual Recognition CVPR 2017 GPflow: A Gaussian Process Library using TensorFlow JMLR 2017 Grammar Variational Autoencoder ICML 2017 Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery Interspeech 2017 Hierarchical Implicit Models and Likelihood-Free Variational Inference NeurIPS 2017 Improved Variational Autoencoders for Text Modeling using Dilated Convolutions ICML 2017 Inference Compilation and Universal Probabilistic Programming AISTATS 2017 Infinite Variational Autoencoder for Semi-Supervised Learning CVPR 2017 Latent Intention Dialogue Models ICML 2017 Learning Discourse-level Diversity for Neural Dialog Models using Conditional Variational Autoencoders ACL 2017 Learning Disentangled Representations with Semi-Supervised Deep Generative Models NeurIPS 2017 Learning Diverse Image Colorization CVPR 2017 Learning Latent Representations for Speech Generation and Transformation Interspeech 2017 Learning Structured Weight Uncertainty in Bayesian Neural Networks AISTATS 2017 Multiplicative Normalizing Flows for Variational Bayesian Neural Networks ICML 2017 Multi-space Variational Encoder-Decoders for Semi-supervised Labeled Sequence Transduction ACL 2017 Neural Discrete Representation Learning NeurIPS 2017 Neural Variational Inference and Learning in Undirected Graphical Models NeurIPS 2017 Non-parametric Structured Output Networks NeurIPS 2017