Here's how AI could help astronomers unlock new secrets about meteors

Astronomers in Arizona turned to artificial intelligence to test out a new method of classifying meteors based on their ...
Nature

Machine learning and data-driven methods in computational surface and interface science

Many modern technological challenges crucially depend on the properties of surfaces and interfaces. This includes the control of charge and energy transfer across electrode/electrolyte interfaces in ...
Nature

Applying interpretable machine learning in computational biology—pitfalls, recommendations and opportunities for new developments

Machine learning has greatly shaped the landscape of computational biology, with the integration of high-throughput data acquisition and burgeoning computational power leading to the creation of ...

Even weak ocean models can provide valuable information for environmental forecasts, study shows

Oxygen depletion in the western Baltic Sea is not uncommon. Oxygen-poor conditions regularly occur in deeper waters, placing ...
Medical Xpress

Integrating machine learning with statistical methods enhances disease risk prediction models

Researchers from Peking University have conducted a comprehensive systematic review on the integration of machine learning into statistical methods for disease risk prediction models, shedding light ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
Frontiers

Advancing Machine Learning for Space Weather Forecasting: Integrating Solar Observations, Geomagnetic Storm Prediction, and GNSS Ionospheric Forecasting

Space weather forecasting remains a major challenge in heliophysics, as geomagnetic storms continue to pose significant risks to satellite operations, power ...
Phys.org

Machine learning method improves accuracy of inverse protein folding for drug design

An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments. Inverse protein folding is a critical ...

Pengwei Zhu Highlights the Role of Deep Statistical Machine Learning in Asthma Research and Target Discovery

A study on high-concurrency payment systems proposes a distributed architecture with layered consistency control to ...
Michigan Technological University

Researchers Apply Machine Learning and AI in Search of Less Costly Electronic Structure Method

Electron density prediction for a four-million-atom aluminum system using machine learning, deemed to be infeasible using traditional DFT method. × Researchers from Michigan Tech and the University of ...
Aalto University

Several Postdoctoral researcher and 1-2 doctoral researcher positions in machine learning in Kaski Lab, ELLIS Institute Finland and Manchester Centre for AI Fundamentals

Samuel Kaski’s two-part research lab in ELLIS Institute Finland (Probabilistic Machine Learning, Aalto University) and the Centre for AI Fundamentals in University of Manchester, is searching for ...