暂无分享,去创建一个
[1] Graham Neubig,et al. Lagging Inference Networks and Posterior Collapse in Variational Autoencoders , 2019, ICLR.
[2] Alexander M. Rush,et al. Semi-Amortized Variational Autoencoders , 2018, ICML.
[3] Andreas Krause,et al. Learning Implicit Generative Models Using Differentiable Graph Tests , 2017, ArXiv.
[4] Zhiting Hu,et al. Improved Variational Autoencoders for Text Modeling using Dilated Convolutions , 2017, ICML.
[5] Qi Liu,et al. Constrained Graph Variational Autoencoders for Molecule Design , 2018, NeurIPS.
[6] Oriol Vinyals,et al. Neural Discrete Representation Learning , 2017, NIPS.
[7] Stefano Ermon,et al. InfoVAE: Balancing Learning and Inference in Variational Autoencoders , 2019, AAAI.
[8] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[9] Alexander M. Rush,et al. Avoiding Latent Variable Collapse With Generative Skip Models , 2018, AISTATS.
[10] Andriy Mnih,et al. Resampled Priors for Variational Autoencoders , 2018, AISTATS.
[11] David Vázquez,et al. PixelVAE: A Latent Variable Model for Natural Images , 2016, ICLR.
[12] S. Ermon,et al. The Information-Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Modeling , 2018 .
[13] Samy Bengio,et al. Generating Sentences from a Continuous Space , 2015, CoNLL.
[14] Christopher Burgess,et al. beta-VAE: Learning Basic Visual Concepts with a Constrained Variational Framework , 2016, ICLR 2016.
[15] Ali Razavi,et al. Preventing Posterior Collapse with delta-VAEs , 2019, ICLR.
[16] Pieter Abbeel,et al. Variational Lossy Autoencoder , 2016, ICLR.
[17] Stefano Ermon,et al. Towards Deeper Understanding of Variational Autoencoding Models , 2017, ArXiv.
[18] Max Welling,et al. VAE with a VampPrior , 2017, AISTATS.