Abstract: In the realm of deep learning, the veracity and integrity of the training data are pivotal for constructing reliable and transparent models. This study introduces the concept of Trustworthy ...

We present the first representative international data on firm-level AI use. We survey almost 6000 CFOs, CEOs and executives from stratified firm samples across the US, UK, Germany and Australia. We ...

Abstract: This study examines the impact of preprocessing techniques, including stratification, oversampling (SMOTE), undersampling, and PCA, on neural network performance for early detection of type ...

DynPricing Dataset v1.0.0 is a processed and structured dataset designed for research in Dynamic Pricing using Reinforcement Learning (RL) and Sequential Decision-Making under Economic Uncertainty.