Models

A Distributed Variational Inference Framework for Unifying Parallel Sparse Gaussian Process Regression Models ICML 2016 A Feature Study for Masking-Based Reverberant Speech Separation Interspeech 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 An Architecture for Deep, Hierarchical Generative Models NeurIPS 2016 An Iterative Phase Recovery Framework with Phase Mask for Spectral Mapping with an Application to Speech Enhancement Interspeech 2016 An Online Sequence-to-Sequence Model Using Partial Conditioning NeurIPS 2016 A Novel Research to Artificial Bandwidth Extension Based on Deep BLSTM Recurrent Neural Networks and Exemplar-Based Sparse Representation Interspeech 2016 A Powerful Generative Model Using Random Weights for the Deep Image Representation NeurIPS 2016 A Probabilistic Framework for Deep Learning NeurIPS 2016 Assessing Speech Quality in Speech-Aware Hearing Aids Based on Phoneme Posteriorgrams Interspeech 2016 A Theory of Generative ConvNet ICML 2016 Attend, Infer, Repeat: Fast Scene Understanding with Generative Models NeurIPS 2016 Augmentable Gamma Belief Networks JMLR 2016 Autoencoding beyond pixels using a learned similarity metric ICML 2016 Auxiliary Deep Generative Models ICML 2016 BayesPy: Variational Bayesian Inference in Python JMLR 2016 Bidirectional Helmholtz Machines ICML 2016 Cells in Multidimensional Recurrent Neural Networks JMLR 2016 Clamping Improves TRW and Mean Field Approximations AISTATS 2016 Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis CVPR 2016 Conditional Generative Moment-Matching Networks NeurIPS 2016 Conditional Image Generation with PixelCNN Decoders NeurIPS 2016 Coupled Generative Adversarial Networks NeurIPS 2016 Deep Gaussian Conditional Random Field Network: A Model-Based Deep Network for Discriminative Denoising CVPR 2016 Deep Learning Games NeurIPS 2016