Current neural network architectures expanded to learn continuous scientific functions

This framework, by enabling AI systems to model the physical world via continuous functions, provides high accuracy even under resolution changes and offers an approach that accelerates traditional simulations in fields such as nuclear chemistry and fluid dynamics by millions of times.