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 Bpapa | $40.19% |
 Queen009 | $20.11% |
 Fumbles | $0.980.05% |
| $0.580.03% | |
 sistrfistr | $0.340.02% |
 dirkjeeter | $0.250.01% |
 P38Srp | $0.240.01% |
 ccog001 | $0.150.01% |
 516 | $0.120.01% |
 7ufJqe | $0.040.00% |
 kyyyy | $0.040.00% |
 hzhsh | $0.030.00% |
 milax | $0.010.00% |
 xpfpf7 | $0.000.00% |
 laylobster61313 | $0.000.00% |
 foresttt | $0.000.00% |
 oh_ffs_ugh | $0.000.00% |
 pezzz | $0.000.00% |
A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence.[1][2] The concept was initially developed by Ian Goodfellow and his colleagues in June 2014.[3] In a GAN, two neural networks contest with each other in the form of a zero-sum game, where one agent's gain is another agent's loss.