Models

Linear dynamical neural population models through nonlinear embeddings NeurIPS 2016 Longitudinal Face Modeling via Temporal Deep Restricted Boltzmann Machines CVPR 2016 Maximum a posteriori Based Decoding for CTC Acoustic Models Interspeech 2016 MDL-CW: A Multimodal Deep Learning Framework With Cross Weights CVPR 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 On Sparse Variational Methods and the Kullback-Leibler Divergence between Stochastic Processes AISTATS 2016 Operator Variational Inference NeurIPS 2016 Pixel Recurrent Neural Networks ICML 2016 Professor Forcing: A New Algorithm for Training Recurrent Networks NeurIPS 2016 Relationship between PreTraining and Maximum Likelihood Estimation in Deep Boltzmann Machines AISTATS 2016 Rényi Divergence Variational Inference NeurIPS 2016 Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages 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 Sequential Neural Models with Stochastic Layers NeurIPS 2016 Speech Bandwidth Extension Using Bottleneck Features and Deep Recurrent Neural Networks Interspeech 2016 Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm NeurIPS 2016 Stochastic Neural Networks with Monotonic Activation Functions AISTATS 2016