Essays about: "Wasserstein Generative Adversarial Network WGAN"
Found 5 essays containing the words Wasserstein Generative Adversarial Network WGAN.
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1. Scenario Generation for Stress Testing Using Generative Adversarial Networks : Deep Learning Approach to Generate Extreme but Plausible Scenarios
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : Central Clearing Counterparties play a crucial role in financial markets, requiring robust risk management practices to ensure operational stability. A growing emphasis on risk analysis and stress testing from regulators has led to the need for sophisticated tools that can model extreme but plausible market scenarios. READ MORE
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2. Fast Simulations of Radio Neutrino Detectors : Using Generative Adversarial Networks and Artificial Neural Networks
University essay from Uppsala universitet/HögenergifysikAbstract : Neutrino astronomy is expanding into the ultra-high energy (>1017eV) frontier with the use of in-ice detection of Askaryan radio emission from neutrino-induced particle showers. There are already pilot arrays for validating the technology and the next few years will see the planning and construction of IceCube-Gen2, an upgrade to the current neutrino telescope IceCube. READ MORE
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3. Instability of a bi-directional TiFGAN in unsupervised speech representation learning
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : A major challenge in the application of machine learning in the speech domain is the unavailability of annotated data. Supervised machine learning techniques are highly dependent on the amount of labelled data and the quality of the labels. READ MORE
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4. Investigating the Learning Behavior of Generative Adversarial Networks
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Since their introduction in 2014, generative adversarial networks (GANs) have quickly become one of the most popular and successful frameworks for training deep generative models. GANs have shown exceptional results on different image generation tasks and they are known for their ability to produce realistic high- resolution images. READ MORE
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5. COMPARISON OF GENERATIVE ADVERSARIAL NETWORKS IN MEDICAL IMAGING APPLICATIONS - MR to CT image synthesis
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Cancer is one of the leading causes of death worldwide with about half of all cancer patients undergoing radiation therapy, either as a standalone treatmentor in combination with other methods such as chemotherapy. The dose planning of radiation therapy is based on medical images such as CT and MR images. READ MORE
