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Algorithmic trading has been increasingly used by Americans. In this work, we tested whether including the opening, closing, and highest prices in three supervised learning models affected their performance. Indeed, we found that including all three prices decreased the error of the prediction significantly.

The authors looked at ways to provide better forecasting on website traffic. They found that deep learning models performed better than statistical models.

The authors looked at different ways to build computational resources that would analyze shooting form for basketball players.

The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.

In this study, the authors share their work on improving the frame rate of videos to reduce data sent to users with both 2D and 3D footage. This work helps improve the experience for both types of footage!

Using machine learning to predict the risk of algae bloom

Here, the authors sought to investigate the effects of water current on the growth of colonies of duckweed, a floating plant that forms colonies in silent ponds, marshes, lakes , and streams in North America. They found that current flow mediates the formation of colonies, disrupting and recreating the colonies which provides the opportunity for reorganizations that were identified as beneficial.

The authors developed a quantum inspired model for stock market fluctuations.

This study uses interpretable machine learning models, lasso and ridge regression with Shapley analysis, to identify key sales drivers for Corporación Favorita, Ecuador’s largest grocery chain. The results show that macroeconomic factors, especially labor force size, have the greatest impact on sales, though geographic and seasonal variables like city altitude and holiday proximity also play important roles. These insights can help businesses focus on the most influential market conditions to enhance competitiveness and profitability.

The authors use pictures of candy wrappers and neural networks to improve nutritional accuracy of diet-tracking apps.