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Despite the tremendous progress in the estimation of generative models, the development of tools for diagnosing their failures and assessing their performance has advanced at a much slower pace.
On measures of information and entropy
Rényi, A. (1961) · 1961
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Expectation propagation for approximate bayesian inference
Minka, T. P. (2001) · 2001
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Information projections revisited
Csiszár, I. and Matus, F. (2003) · 2003
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Convex optimization
Boyd, S. and Vandenberghe, L. (2004) · 2004
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Clustering with bregman divergences
Banerjee, A., Merugu, S., Dhillon, I. S., and Ghosh, J. (2005) · 2005
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Divergence measures and message passing
Minka, T. et al. (2005) · 2005
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On the centroids of symmetrized Bregman divergences
Nielsen, F. and Nock, R. (2007) · 2007
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Graphical models, exponential families, and variational inference
Wainwright, M. J., Jordan, M. I., et al. (2008) · 2008
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The dual Voronoi diagrams with respect to representational Bregman divergences
Nielsen, F. and Nock, R. (2009) · 2009
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When Data Compression and Statistics Disagree
van Erven, T. (2010) · 2010
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Density ratio estimation in machine learning
Sugiyama, M., Suzuki, T., and Kanamori, T. (2012) · 2012
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Rényi divergence measures for commonly used univariate continuous distributions
Gil, M., Alajaji, F., and Linder, T. (2013) · 2013
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Auto-encoding variational Bayes
Kingma, D. P. and Welling, M. (2013) · 2013
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The funk and hilbert geometries for spaces of constant curvature
Papadopoulos, A. and Yamada, S. (2013) · 2013
Cited alongside, same era.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y. (2014) · 2014
Rényi divergence variational inference
Li, Y. and Turner, R. E. (2016) · 2016
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Linking losses for density ratio and class-probability estimation
Menon, A. and Ong, C. S. (2016) · 2016
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Improved techniques for training gans
Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., and Chen, X. (2016) · 2016
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Heusel, M., Ramsauer, H., Unterthiner, T., Nessler, B., and Hochreiter, S. (2017) · 2017
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Are GANs Created Equal? A Large-Scale Study
Lucic, M., Kurach, K., Michalski, M., Gelly, S., and Bousquet, O. (2018) · 2018
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Assessing generative models via precision and recall
Sajjadi, M. S., Bachem, O., Lucic, M., Bousquet, O., and Gelly, S. (2018) · 2018
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Cited alongside, same era.
Papadopoulos, A. and Troyanov, M. (2014) · 2014
Cited alongside, same era.
Stochastic backpropagation and approximate inference in deep generative models
Rezende, D. J., Mohamed, S., and Wierstra, D. (2014) · 2014
Cited alongside, same era.
Rényi divergence and kullback-leibler divergence
Van Erven, T. and Harremos, P. (2014) · 2014
Cited alongside, same era.
Later among the works it cites.
Improved precision and recall metric for assessing generative models
Kynkäänniemi, T., Karras, T., Laine, S., Lehtinen, J., and Aila, T. (2019) · 2019
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Revisiting precision recall definition for generative modeling
Simon, L., Webster, R., and Rabin, J. (2019) · 2019
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