Science

A new principle, Neural Coherence, offers a way to boost model performance on unseen tasks by strategically selecting pre-trained models and data.

A new review explores how quantifying uncertainty can unlock data-efficient artificial intelligence, enabling robust performance even with limited training data.

A new approach to detecting AI-generated images focuses on the subtle fingerprints left by camera hardware, rather than the telltale signs of the generative model itself.

As demand for robust facial recognition systems grows, researchers are increasingly turning to artificially generated datasets to overcome limitations in real-world training data.

Researchers are leveraging the power of artificial intelligence to reverse-engineer the complex processes that lead to the formation of exoplanets.

New research demonstrates that intentionally introducing ‘imperfect’ data can significantly improve the robustness and accuracy of time series forecasting models.

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.