Generative Models

Learning Deep Sigmoid Belief Networks with Data Augmentation AISTATS 2015 Learning Structured Output Representation using Deep Conditional Generative Models NeurIPS 2015 Learning to Generate Chairs With Convolutional Neural Networks CVPR 2015 Learning to Linearize Under Uncertainty NeurIPS 2015 Listening With Your Eyes: Towards a Practical Visual Speech Recognition System Using Deep Boltzmann Machines ICCV 2015 MADE: Masked Autoencoder for Distribution Estimation ICML 2015 Max-Margin Deep Generative Models NeurIPS 2015 On Theoretical Properties of Sum-Product Networks AISTATS 2015 Regularizing Max-Margin Exemplars by Reconstruction and Generative Models CVPR 2015 Similarity-based Contrastive Divergence Methods for Energy-based Deep Learning Models ACML 2015 Texture Synthesis Using Convolutional Neural Networks NeurIPS 2015 The Poisson Gamma Belief Network NeurIPS 2015 The Return of the Gating Network: Combining Generative Models and Discriminative Training in Natural Image Priors NeurIPS 2015 Training Restricted Boltzmann Machine via the Thouless-Anderson-Palmer free energy NeurIPS 2015 Unsupervised Learning by Program Synthesis NeurIPS 2015 Unsupervised Semantic Parsing of Video Collections ICCV 2015 Variational Generative Stochastic Networks with Collaborative Shaping ICML 2015 Blind Image Quality Assessment using Semi-supervised Rectifier Networks CVPR 2014 Convolutional Kernel Networks NeurIPS 2014 Deep AutoRegressive Networks ICML 2014 Deep Generative Stochastic Networks Trainable by Backprop ICML 2014 Deep Supervised and Convolutional Generative Stochastic Network for Protein Secondary Structure Prediction ICML 2014 Factoring Variations in Natural Images with Deep Gaussian Mixture Models NeurIPS 2014 General Stochastic Networks for Classification NeurIPS 2014 Generative Adversarial Nets NeurIPS 2014