Models

Stochastic Variational Deep Kernel Learning NeurIPS 2016 Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors ICML 2016 Structured Generative Models of Continuous Features for Word Sense Induction COLING 2016 Synthesizing the preferred inputs for neurons in neural networks via deep generator networks NeurIPS 2016 TensorFlow: A System for Large-Scale Machine Learning OSDI 2016 Texture Networks: Feed-forward Synthesis of Textures and Stylized Images ICML 2016 The Generalized Reparameterization Gradient NeurIPS 2016 Tight Variational Bounds via Random Projections and I-Projections AISTATS 2016 Towards Conceptual Compression NeurIPS 2016 Universal Approximation Results for the Temporal Restricted Boltzmann Machine and the Recurrent Temporal Restricted Boltzmann Machine JMLR 2016 Unsupervised Learning of 3D Structure from Images NeurIPS 2016 Variational Autoencoder for Deep Learning of Images, Labels and Captions NeurIPS 2016 Variational Bayes on Monte Carlo Steroids NeurIPS 2016 Variational Dependent Multi-output Gaussian Process Dynamical Systems JMLR 2016 Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes JMLR 2016 Variational Inference for Monte Carlo Objectives ICML 2016 Variational Inference in Mixed Probabilistic Submodular Models NeurIPS 2016 Variational Tempering AISTATS 2016 Visual Dynamics: Probabilistic Future Frame Synthesis via Cross Convolutional Networks NeurIPS 2016 Voice Conversion Based on Trajectory Model Training of Neural Networks Considering Global Variance Interspeech 2016 Wasserstein Training of Restricted Boltzmann Machines NeurIPS 2016 Weakly-supervised text-to-speech alignment confidence measure COLING 2016 Accurate and conservative estimates of MRF log-likelihood using reverse annealing AISTATS 2015 A Recurrent Latent Variable Model for Sequential Data NeurIPS 2015 Are You Talking to a Machine? Dataset and Methods for Multilingual Image Question NeurIPS 2015