Adversarial generation of extreme samples
Modelling extreme events in order to evaluate and mitigate their risk is a fundamental goal in many areas, including extreme weather events, financial crashes, and unexpectedly high demand for online services. In order to mitigate such risk it is vital to be able to generate a wide range of extreme, and realistic, scenarios. Researchers from … Continue reading Adversarial generation of extreme samples
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