Scientific discovery in the age of artificial intelligence

H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu… - Nature, 2023 - nature.com
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …

Neural operators for accelerating scientific simulations and design

K Azizzadenesheli, N Kovachki, Z Li… - Nature Reviews …, 2024 - nature.com
Scientific discovery and engineering design are currently limited by the time and cost of
physical experiments. Numerical simulations are an alternative approach but are usually …

Kan: Kolmogorov-arnold networks

Z Liu, Y Wang, S Vaidya, F Ruehle, J Halverson… - ar**s between function spaces and offer a new
simulation paradigm for real-time prediction of complex dynamics for realistic diverse …

Physics-informed neural operator for learning partial differential equations

Z Li, H Zheng, N Kovachki, D **, H Chen… - ACM/JMS Journal of …, 2024 - dl.acm.org
In this article, we propose physics-informed neural operators (PINO) that combine training
data and physics constraints to learn the solution operator of a given family of parametric …