Enhancing machine-learning interatomic potentials for advanced materials modeling

Machine learning is transforming many scientific fields, including computational materials science. For about two decades, ...

Quantum machine learning nears practicality as partial error correction reduces hardware demands

Imagine a future where quantum computers supercharge machine learning—training models in seconds, extracting insights from ...
Semiconductor Engineering

AI Meets Device Modeling: Transforming Compact Modeling With Machine Learning

As semiconductor technologies advance, device structures are becoming increasingly complex. New materials and architectures introduce intricate physical effects requiring accurate modeling to ensure ...
International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...
Science Daily

Improving hurricane modeling with physics-informed machine learning

Researchers employ machine learning to more accurately model the boundary layer wind field of tropical cyclones. Conventional approaches to storm forecasting involve large numerical simulations run on ...
The Lancet

Effective sample size for individual risk predictions: quantifying uncertainty in machine learning models

Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
AZoLifeSciences on MSN

Machine Learning Model Accounts for Biological Variability in Culture Media Design

Cell culture is a foundational technology widely used across fields such as pharmaceutical production, regenerative medicine, food science, and materials engineering. A critical component of ...