This paper explores deep learning (DL) methods that are used or have the potential to be
used for traffic video analysis, emphasising driving safety for both autonomous vehicles and …

Attributions are a common local explanation technique for deep learning models on single
samples as they are easily extractable and demonstrate the relevance of input values. In …

With the rising need of interpretable machine learning methods, there is a necessity for a
rise in human effort to provide diverse explanations of the influencing factors of the model …

Price prediction remains a crucial aspect of financial market research as it forms the basis for
various trading strategies and portfolio management techniques. However, traditional …

Abstract Explainable Artificial Intelligence (XAI) has gained significant attention recently as
the demand for transparency and interpretability of machine learning models has increased …

Hedging against price increases is particularly important in times of significant market
uncertainty and price volatility. For commodity procuring firms, futures contracts are a …

Among recent developments in time series forecasting methods, deep forecasting models
have gained popularity as they can utilize hidden feature patterns in time series to improve …

Abstract Explainable Artificial Intelligence (XAI) techniques are used to provide transparency
to complex, opaque predictive models. However, these techniques are often designed for …

Artificial Intelligence (AI) models have reached a very significant level of accuracy. While
their superior performance offers considerable benefits, their inherent complexity often …

The advent of Transformer architectures has ushered in a new era across various domains,
including finance. These Transformer models, renowned for their scalability and efficacy, are …