Machine learning is transforming many scientific fields, including computational materials science. For about two decades, scientists have been using it to make accurate yet inexpensive calculations ...

MIT researchers have developed a method that generates more accurate uncertainty measures for certain types of estimation.

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

Quantum physics has a reputation for needing exotic hardware, from liquid-helium-cooled qubits to sprawling AI clusters, just ...

Future events such as the weather or satellite trajectories are computed in tiny time steps, so the computation must be both ...

An unexpected anomaly is only as disruptive as the framework it challenges, and in modern physics that framework is a ...

To cite the contents of this repository, please cite both the paper and the INFORMS Journal on Computing GitHub repo, using their respective DOIs.

Abstract: We propose an online learning algorithm tailored for a class of machine learning models within a separable stochastic approximation framework. The central idea of our approach is to exploit ...

Forget 30, flirty, and thriving—you’re 40 and ready to have the fittest years of your life. Maybe, after years of caring for young children, you’ve mastered the morning school drop-off and have ...

The Magnetic Flux Rope Models is a Python package whose aim is to provide a simple and reliable way to work with analytical magnetic flux rope models. It can be used to simply explore and visualise ...

Abstract: Kernel extreme learning machine (KELM) not only inherits the high learning efficiency of the traditional extreme learning machine (ELM), but also mitigates the instability caused by random ...

ABSTRACT: With the rapid development of science and technology, artificial intelligence plays a significant role across various domains. In recent years, frequent occurrences of natural disasters and ...