Generative adversarial network

A generative adversarial network (GAN) is a class of machine learning frameworks designed by Ian Goodfellow and his colleagues in 2014. Two neural networks contest with each other in a game (in the form of a zero-sum game, where one agent's gain is another agent's loss).

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Total Publications

Lifetime

7,185

Prior Five Years

4,976

Total Citations

Lifetime

80,767

Prior Five Years

77,366

Total Scholars

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13,990

Prior Five Years

13,869

Institutional Rankings

Global (Worldwide)

Academic Institutions Lifetime		Academic Institutions Prior Five Years		Non-academic Institutions Lifetime
#1	Imperial College London United Kingdom	#1	Imperial College London United Kingdom	#1	Nvidia Corporation United States
#2	Rutgers, The State University of New Jersey United States	#2	Rutgers, The State University of New Jersey United States	#2	Lawrence Berkeley National Laboratory United States
#3	Harbin Institute of Technology China	#3	Harbin Institute of Technology China	#3	International Business Machines Corporation United States
#4	University of Trento Italy	#4	University of Trento Italy	#4	Nippon Telegraph and Telephone Corporation Japan
#5	Wuhan University China	#5	Wuhan University China	#5	Tencent Holdings Ltd. China
#6	Institute of Automation, Chinese Academy of Sciences China	#6	Institute of Automation, Chinese Academy of Sciences China	#6	Huawei Technologies Co. China
#7	Polytechnic University of Catalonia Spain	#7	Polytechnic University of Catalonia Spain		Show More
#8	Lehigh University United States	#8	Lehigh University United States
#9	University of Saskatchewan Canada	#9	University of Saskatchewan Canada
#10	University of Sydney Australia	#10	University of Sydney Australia
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Highly Cited Publications

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