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We generalize gradient descent with momentum for optimization in differentiable games to have complex-valued momentum.
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Generative adversarial nets
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Unrolled generative adversarial networks
Luke Metz, Ben Poole, David Pfau, and Jascha Sohl-Dickstein · 2016
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Improved techniques for training GANs
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, and Xi Chen · 2016
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The numerics of GANs
Lars Mescheder, Sebastian Nowozin, and Andreas Geiger · 2017
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Why momentum really works
Gabriel Goh · 2017
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Automatic differentiation in PyTorch
Adam Paszke, Sam Gross, Soumith Chintala, Gregory Chanan, Edward Yang, Zachary DeVito, Zeming Lin, Alban Desmaison, Luca Antiga, and Adam Lerer · 2017
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Jian Zhang and Ioannis Mitliagkas · 2017
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Intrinsic motivation and automatic curricula via asymmetric self-play
Sainbayar Sukhbaatar, Zeming Lin, Ilya Kostrikov, Gabriel Synnaeve, Arthur Szlam, and Rob Fergus · 2018
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Stochastic hyperparameter optimization through hypernetworks
Jonathan Lorraine and David Duvenaud · 2018
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Will Grathwohl, Elliot Creager, Seyed Kamyar Seyed Ghasemipour, and Richard Zemel · 2018
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