Abstract: Causal inference is an important field in data science and cognitive artificial intelligence. It requires the construction of complex probabilistic models to describe the causal ...

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Among the ten submissions, "How Much?" stood out for its critical examination of the modernist notion of "cheapness," where seemingly cost-effective solutions have often proved expensive socially, ...

Abstract: This article investigates the potential of dual CNN-Transformer architectures for generalizable few-shot anomaly detection (GFSAD), a practical yet understudied form of anomaly detection (AD ...