Fetching the paper…
Reading the bibliography…
Variational autoencoders are powerful algorithms for identifying dominant latent structure in a single dataset.
Silhouettes: a graphical aid to the interpretation and validation of cluster analysis
Rousseeuw, P. J · 1987
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Deng, J., Dong, W., Socher, R., Li, L.-J., Li, K., and Fei-Fei, L · 2009
Earlier work this paper cites.
Mnist handwritten digit database
LeCun, Y., Cortes, C., and Burges, C · 2010
Earlier work this paper cites.
Estimating divergence functionals and the likelihood ratio by convex risk minimization
Nguyen, X., Wainwright, M. J., and Jordan, M. I · 2010
Earlier work this paper cites.
Auto-encoding variational bayes
Kingma, D. P. and Welling, M · 2013
Earlier work this paper cites.
Contrastive learning using spectral methods
Zou, J. Y., Hsu, D. J., Parkes, D. C., and Adams, R. P · 2013
Earlier work this paper cites.
Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2014
Earlier work this paper cites.
Deep learning face attributes in the wild
Liu, Z., Luo, P., Wang, X., and Tang, X · 2015
Cited alongside, same era.
Domain separation networks
Bousmalis, K., Trigeorgis, G., Silberman, N., Krishnan, D., and Erhan, D · 2016
Cited alongside, same era.
Novelty detection and cluster analysis in time series data using variational autoencoder feature maps
Clachar, S · 2016
Cited alongside, same era.
Tutorial on variational autoencoders
Doersch, C · 2016
Cited alongside, same era.
Rich component analysis
Ge, R. and Zou, J · 2016
Cited alongside, same era.
Ladder variational autoencoders
Sønderby, C. K., Raiko, T., Maaløe, L., Sønderby, S. K., and Winther, O · 2016
Cited alongside, same era.
Exploring patterns enriched in a dataset with contrastive principal component analysis
Abid, A., Zhang, M. J., Bagaria, V. K., and Zou, J · 2018
Later among the works it cites.
Isolating sources of disentanglement in variational autoencoders
Chen, T. Q., Li, X., Grosse, R., and Duvenaud, D · 2018
Later among the works it cites.
Contrastive multivariate singular spectrum analysis
Dirie, A.-H., Abid, A., and Zou, J · 2018
Later among the works it cites.
Image-to-image translation for cross-domain disentanglement
Gonzalez-Garcia, A., van de Weijer, J., and Bengio, Y · 2018
Later among the works it cites.
Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell rna transcriptomics
Hu, Q. and Greene, C. S · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Massively parallel digital transcriptional profiling of single cells
Zheng, G. X., Terry, J. M., Belgrader, P., Ryvkin, P., Bent, Z. W., Wilson, R., Ziraldo, S. B., Wheeler, T. D., McDermott, G. P., Zhu, J., et al · 2017
Cited alongside, same era.
Later among the works it cites.
Kim, H. and Mnih, A · 2018
Later among the works it cites.
Unsupervised learning with contrastive latent variable models
Severson, K., Ghosh, S., and Ng, K · 2018
Later among the works it cites.