Variational Autoencoders

Fully Unsupervised Diversity Denoising with Convolutional Variational Autoencoders ICLR 2021 Metric Learning for comparison of HMMs using Graph Neural Networks ACML 2021 On Empirical Bayes Variational Autoencoder: An Excess Risk Bound COLT 2021 Disentangled Representations for Sequence Data using Information Bottleneck Principle ACML 2020 Disentangled Variational Autoencoder based Multi-Label Classification with Covariance-Aware Multivariate Probit Model IJCAI 2020 Generalized Zero-Shot Learning via Over-Complete Distribution CVPR 2020 Theory and Evaluation Metrics for Learning Disentangled Representations ICLR 2020 Variational Template Machine for Data-to-Text Generation ICLR 2020 Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder ICLR 2019 Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders CVPR 2019 Lagging Inference Networks and Posterior Collapse in Variational Autoencoders ICLR 2019 Learning Flexible Latent Representations via Encapsulated Variational Encoders AAAI 2019 Multidimensional Time Series Anomaly Detection: A GRU-based Gaussian Mixture Variational Autoencoder Approach ACML 2018 Attend, Infer, Repeat: Fast Scene Understanding with Generative Models NeurIPS 2016 Towards Conceptual Compression NeurIPS 2016 A Recurrent Latent Variable Model for Sequential Data NeurIPS 2015 Embed to Control: A Locally Linear Latent Dynamics Model for Control from Raw Images NeurIPS 2015