Prediction-powered inference integrates a small gold-standard dataset with a large auxiliary dataset informed by machine ...

Infinite dilution activity coefficient is a key thermodynamic parameter in solvent design for chemical processes. Although ...

In a recent paper, SFI Complexity Postdoctoral Fellow Yuanzhao Zhang and co-author William Gilpin show that a deceptively ...

A high-precision machine learning potential based on the Deep Potential method was constructed to systematically investigate ...

NOTE. These are the baseline variables determined at treatment completion and included in the analysis. Abbreviations: CIN, cervical intraepithelial neoplasia; COPD, chronic obstructive pulmonary ...

Ionospheric delay remains a significant error source in GNSS positioning, particularly for single-frequency users and during periods of enhanced space weather ...

A machine learning model using routine clinical data more accurately predicted 5-year heart failure risk in patients with CKD ...

• A new AI machine learning algorithm capable of predicting planetary orbits that may one day help accelerate physics research in other areas such as renewable energy. • Strikingly, the algorithms ...

Young, T. , Guymon, J. , Pankow, M. and Ngaile, G. (2026) A Material Removal Prediction Framework for Ball EEM Polishing in ...

During the last few years or so more people have been been jumping on the artificial intelligence bandwagon and talking about its potential influence on the planet as a whole. The world is much closer ...