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We present a variety of new architectural features and training procedures that we apply to the generative adversarial networks (GANs) framework. Using our new techniques, we achieve state-of-the-art results in semi-supervised classification on MNIST, CIFAR-10 and SVHN. The generated images are of high quality as confirmed by a visual Turing test: Our model(More)
OpenAI Gym1 is a toolkit for reinforcement learning research. It includes a growing collection of benchmark problems that expose a common interface, and a website where people can share their results and compare the performance of algorithms. This whitepaper discusses the components of OpenAI Gym and the design decisions that went into the software.
The growth of dust particles in a plasma can drastically change the plasma's properties; importantly, it can affect the electron energy distribution function. We have performed optical emission spectroscopy on an RF sputtering discharge in argon during dust particle growth to analyze this change. We find that the intensities of all of the argon emission(More)
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