Generative Models

Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling NeurIPS 2016 Learning Sigmoid Belief Networks via Monte Carlo Expectation Maximization AISTATS 2016 Learning to Generate with Memory ICML 2016 Learning What and Where to Draw NeurIPS 2016 Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines CVPR 2016 Maximum a posteriori Based Decoding for CTC Acoustic Models Interspeech 2016 Modeling and Transforming Speech Using Variational Autoencoders Interspeech 2016 Modelling Symbolic Music: Beyond the Piano Roll ACML 2016 Neural Autoregressive Distribution Estimation JMLR 2016 Neurally-Guided Procedural Models: Amortized Inference for Procedural Graphics Programs using Neural Networks NeurIPS 2016 Neural Universal Discrete Denoiser NeurIPS 2016 Neural Variational Inference for Text Processing ICML 2016 One-Shot Generalization in Deep Generative Models ICML 2016 Online Algorithms for Sum-Product Networks with Continuous Variables PGM 2016 Pixel Recurrent Neural Networks ICML 2016 Professor Forcing: A New Algorithm for Training Recurrent Networks NeurIPS 2016 Semi-Supervised Speaker Adaptation for In-Vehicle Speech Recognition with Deep Neural Networks Interspeech 2016 Semi-Supervised Training in Deep Learning Acoustic Model Interspeech 2016 Speech Bandwidth Extension Using Bottleneck Features and Deep Recurrent Neural Networks Interspeech 2016 Stochastic Neural Networks with Monotonic Activation Functions AISTATS 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 Texture Networks: Feed-forward Synthesis of Textures and Stylized Images ICML 2016 Towards Conceptual Compression NeurIPS 2016 Universal Approximation Results for the Temporal Restricted Boltzmann Machine and the Recurrent Temporal Restricted Boltzmann Machine JMLR 2016