Current machine-learning methods have not contributed to our understanding of fluid mechanics, for example, which is basically governed by one of the most difficult partial differential equations set.
Machine learning is usually used as black box tool and we are more concern on good result i.e good mapping between input space to output space. This is my point of view. Could you elaborate more on what to you mean by understanding of fluid mechanics with examples?
Excellent. Really cool examples!
Thank you! These tools are very useful
So then scale resolution and scale solvers could be a new wave? Intriguing daniele
Current machine-learning methods have not contributed to our understanding of fluid mechanics, for example, which is basically governed by one of the most difficult partial differential equations set.
Machine learning is usually used as black box tool and we are more concern on good result i.e good mapping between input space to output space. This is my point of view. Could you elaborate more on what to you mean by understanding of fluid mechanics with examples?