GenEval: A Benchmark Suite for Evaluating Generative Models
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[1] Martín Abadi,et al. TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems , 2016, ArXiv.
[2] David Lopez-Paz,et al. Revisiting Classifier Two-Sample Tests , 2016, ICLR.
[3] Matthias Bethge,et al. A note on the evaluation of generative models , 2015, ICLR.
[4] Gaël Varoquaux,et al. Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..
[5] Xiaohua Zhai,et al. The GAN Landscape: Losses, Architectures, Regularization, and Normalization , 2018, ArXiv.
[6] Léon Bottou,et al. Wasserstein Generative Adversarial Networks , 2017, ICML.
[7] Max Welling,et al. Auto-Encoding Variational Bayes , 2013, ICLR.
[8] Sebastian Nowozin,et al. Stabilizing Training of Generative Adversarial Networks through Regularization , 2017, NIPS.
[9] E. Parzen. On Estimation of a Probability Density Function and Mode , 1962 .
[10] Yingyu Liang,et al. Generalization and Equilibrium in Generative Adversarial Nets (GANs) , 2017, ICML.
[11] Donald Geman,et al. Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images , 1984 .
[12] Luca Antiga,et al. Automatic differentiation in PyTorch , 2017 .
[13] Mario Lucic,et al. Are GANs Created Equal? A Large-Scale Study , 2017, NeurIPS.
[14] Yoshua Bengio,et al. Generative Adversarial Nets , 2014, NIPS.
[15] Wojciech Zaremba,et al. Improved Techniques for Training GANs , 2016, NIPS.
[16] Yi Zhang,et al. Do GANs actually learn the distribution? An empirical study , 2017, ArXiv.
[17] Rob Fergus,et al. Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks , 2015, NIPS.
[18] Samy Bengio,et al. Density estimation using Real NVP , 2016, ICLR.
[19] D. Rubin,et al. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .
[20] Soumith Chintala,et al. Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks , 2015, ICLR.
[21] Jaakko Lehtinen,et al. Progressive Growing of GANs for Improved Quality, Stability, and Variation , 2017, ICLR.
[22] Aaron C. Courville,et al. Improved Training of Wasserstein GANs , 2017, NIPS.
[23] M. Rosenblatt. Remarks on Some Nonparametric Estimates of a Density Function , 1956 .