Shichang Tang

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All published works

Action	Title	Year	Authors
+	Lessons Learned from the Training of GANs on Artificial Datasets	2020	Shichang Tang
+ PDF Chat	Lessons Learned From the Training of GANs on Artificial Datasets	2020	Shichang Tang

Common Coauthors

Coauthor	Papers Together

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation	2018	Yunjey Choi Minje Choi Munyoung Kim Jung-Woo Ha Sunghun Kim Jaegul Choo	2
+	Residual Flows for Invertible Generative Modeling	2019	Ricky T. Q. Chen Jens Behrmann David Duvenaud Jörn-Henrik Jacobsen	2
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	2
+ PDF Chat	Stacked Generative Adversarial Networks	2017	Xun Huang Yixuan Li Omid Poursaeed John E. Hopcroft Serge Belongie	2
+	Towards Principled Methods for Training Generative Adversarial Networks	2017	Martín Arjovsky Léon Bottou	2
+	NIPS 2016 Tutorial: Generative Adversarial Networks	2017	Ian Goodfellow	2
+ PDF Chat	Least Squares Generative Adversarial Networks	2017	Xudong Mao Qing Li Haoran Xie Raymond Y.K. Lau Zhen Wang Stephen Paul Smolley	2
+	Which Training Methods for GANs do actually Converge?	2018	Lars Mescheder Andreas Geiger Sebastian Nowozin	2
+ PDF Chat	AutoGAN: Neural Architecture Search for Generative Adversarial Networks	2019	Xinyu Gong Shiyu Chang Yifan Jiang Zhangyang Wang	2
+	LOGAN: Latent Optimisation for Generative Adversarial Networks	2019	Yan Wu Jeff Donahue David Balduzzi Karen Simonyan Timothy Lillicrap	2
+	Consistency Regularization for Generative Adversarial Networks	2019	Han Zhang Zizhao Zhang Augustus Odena Honglak Lee	2
+ PDF Chat	Rethinking the Inception Architecture for Computer Vision	2016	Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jon Shlens Zbigniew Wojna	2
+ PDF Chat	A Style-Based Generator Architecture for Generative Adversarial Networks	2019	Tero Karras Samuli Laine Timo Aila	2
+ PDF Chat	Multi-agent Diverse Generative Adversarial Networks	2018	Arnab Ghosh Viveka Kulharia Vinay P. Namboodiri Philip H. S. Torr Puneet K. Dokania	2
+	Do GANs actually learn the distribution? An empirical study	2017	Sanjeev Arora Yi Zhang	2
+	Improved Techniques for Training GANs	2016	Tim Salimans Ian Goodfellow Wojciech Zaremba Vicki Cheung Alec Radford Xi Chen	2
+	Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift	2015	Sergey Ioffe Christian Szegedy	2
+	GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium	2017	Martin Heusel Hubert Ramsauer Thomas Unterthiner Bernhard Nessler Sepp Hochreiter	1
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	1
+	Large Scale Adversarial Representation Learning	2019	Jeff Donahue Karen Simonyan	1
+	Generative Modeling by Estimating Gradients of the Data Distribution	2019	Yang Song Stefano Ermon	1
+	Generating Diverse High-Fidelity Images with VQ-VAE-2	2019	Ali Razavi Aäron van den Oord Oriol Vinyals	1
+	Glow: Generative Flow with Invertible 1x1 Convolutions	2018	Diederik P. Kingma Prafulla Dhariwal	1
+	Class-Splitting Generative Adversarial Networks	2017	Guillermo L. Grinblat Lucas C. Uzal Pablo M. Granitto	1
+	Comparison of Maximum Likelihood and GAN-based training of Real NVPs	2017	Ivo Danihelka Balaji Lakshminarayanan Benigno Uría Daan Wierstra Peter Dayan	1
+	Progressive Growing of GANs for Improved Quality, Stability, and Variation	2017	Tero Karras Timo Aila Samuli Laine Jaakko Lehtinen	1
+	Improved Training of Wasserstein GANs	2017	Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville	1
+	GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium	2017	Martin Heusel Hubert Ramsauer Thomas Unterthiner Bernhard Nessler Sepp Hochreiter	1
+	Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks	2016	Tim Salimans Diederik P. Kingma	1
+	Comparison of Maximum Likelihood and GAN-based training of Real NVPs.	2017	Ivo Danihelka Balaji Lakshminarayanan Benigno Uría Daan Wierstra Peter Dayan	1
+	Class-Splitting Generative Adversarial Networks.	2017	Guillermo L. Grinblat Lucas C. Uzal Pablo M. Granitto	1
+	A Note on the Inception Score	2018	Shane Barratt Rishi Sharma	1
+	Spectral Normalization for Generative Adversarial Networks	2018	Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida	1
+	cGANs with Projection Discriminator	2018	Takeru Miyato Masanori Koyama	1
+	Large Scale GAN Training for High Fidelity Natural Image Synthesis	2018	Andrew Brock Jeff Donahue Karen Simonyan	1
+	Generating Diverse High-Fidelity Images with VQ-VAE-2	2019	Ali Razavi Aäron van den Oord Oriol Vinyals	1
+	Generative Multi-Adversarial Networks	2016	Ishan Durugkar Ian Gemp Sridhar Mahadevan	1
+	Conditional Image Synthesis With Auxiliary Classifier GANs	2016	Augustus Odena Christopher Olah Jonathon Shlens	1
+	Large Scale GAN Training for High Fidelity Natural Image Synthesis	2018	Andrew Brock Jeff Donahue Karen Simonyan	1
+	Stabilizing Training of Generative Adversarial Networks through Regularization	2017	Kevin A. Roth Aurélien Lucchi Sebastian Nowozin Thomas Hofmann	1
+	Large Scale Adversarial Representation Learning	2019	Jeff Donahue Karen Simonyan	1
+	Generative Modeling by Estimating Gradients of the Data Distribution	2019	Yang Song Stefano Ermon	1
+	Glow: Generative Flow with Invertible 1x1 Convolutions	2018	Diederik P. Kingma Prafulla Dhariwal	1
+	Spectral Normalization for Generative Adversarial Networks	2018	Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida	1