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 in image domains%2C our research extends its principles to tabular data. Our contributions include adapting AnoGAN's principles to a new domain and promising advancements in detecting previously undetectable anomalies. This paper delves into the multifaceted nature of anomaly detection%2C considering the dynamic evolution of normal behavior%2C context-dependent anomaly definitions%2C and data-related challenges like noise and imbalances.?quality=80&w=800)
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