Machine learning rediscovers equations governing ocean biogeochemistry

Climate and ocean models use a series of equations to represent complex natural processes. However, the equations used in ...
Nature

Machine learning based on a generative adversarial tri-model

This paper proposes a novel machine learning paradigm called the generative adversarial tri-model (GAT) to incorporate analytical knowledge into neural networks through a unique positive-sum game ...

The weather and climate science AI revolution isn’t revolutionary

It feels like there’s no escaping AI right now, whether you’re trying to type a sentence without being interrupted by a digital “assistant” or struggling to find a new refrigerator that doesn’t ...
Nature

Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks

In an era marked by exponential data growth and pervasive digital connectivity, understanding the intricate structure of networks has become a critical challenge across various domains. Whether ...
Phys.org

Ultra‑robust machine‑learning models run stable molecular simulations at extreme temperatures

Researchers at The University of Manchester have created a physics‑informed machine‑learning model that can run molecular simulations for unprecedented lengths of time, even at temperatures as high as ...
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 ...