In stock market forecasting, the identification of critical features that affect the performance of
machine learning (ML) models is crucial to achieve accurate stock price predictions. Several …

Autoencoders are a self-supervised learning system where, during training, the output is an
approximation of the input. Typically, autoencoders have three parts: Encoder (which …

In recent years, human health across the world is becoming concerned by a constant threat
of air pollution, which causes many chronic diseases and premature mortalities. Poor air …

This study focuses on explainable artificial intelligence (XAI) in finance. We collected 2,733
articles published between 2013 and 2023 from the Web of Science Core Collection and …

Accurate prediction of the stock market trend can assist efficient portfolio and risk
management. In recent years, with the rapid development of deep learning, it can make the …

Market prediction has been a key interest for professionals around the world. Numerous
modern technologies have been applied in addition to statistical models over the years …

Prediction with higher accuracy is vital for stock market prediction. Recently, considerable
amount of effort has been poured into employing machine learning (ML) techniques for …

In recent times, microarray gene expression datasets have gained significant popularity due
to their usefulness to identify different types of cancer directly through bio-markers. These …

Forecasting of future stock prices is a complex and challenging research problem due to the
random variations that the time series of these variables exhibit. In this work, we study the …

Video prediction is extremely challenging in a traffic flow forecasting problem due to
dynamic spatiotemporal dependence. Eidetic 3D convolutional long short-term memory …