Science

A new deep learning model leverages survival analysis to forecast the likelihood of limit orders being filled, offering a powerful tool for algorithmic trading.

A novel deep learning framework accurately forecasts the return on investment for Bitcoin mining hardware, helping operators make smarter, data-driven decisions.

A novel machine learning approach leveraging likelihood ratios significantly improves the accuracy of financial derivative pricing, particularly for complex contracts.

A new framework bridges the gap between agent-based simulations and deep learning to create more interpretable and reliable models of complex systems.

New research shows that artificial intelligence can intelligently allocate funds within mutual fund portfolios to maximize returns while minimizing risk.

New research demonstrates that spiking neural networks, modeled on the human brain, can anticipate rapid price changes in high-frequency trading with improved accuracy.

Researchers have developed a novel approach to enhance the realism and variability of predicted human movements in videos, achieving compelling results without the need for extensive retraining.

New research presents a highly adaptable detection system designed to identify and mitigate the growing threat of compromised Python packages used in enterprise software.

Researchers have developed a novel network architecture that efficiently fuses multi-frequency image data to achieve high-accuracy, real-time stereo matching.

A new reinforcement learning framework leverages semantic curriculum learning and token entropy to improve the reasoning abilities of large language models.