PINNs
topic on 1 show · 2 statements across 1 episodes
2 statements about PINNs, every show
Neural operators overcome PINN limitations by combining data with physics constraints
“Our idea of neural operators came as a way to overcome this, right? So saying, you know, we can't rely just on physics constraints alone to come up with answers. We have lots of data available. You know, I'll talk about the weather example where we even collec…”
Physics-Informed Neural Networks fail on chaotic, time-dependent differential equations
“Optimization ends up being usually very difficult, especially for problems that are time-dependent, meaning it's not just stationary, you also have time, and the time component in many cases could be turbulent, like in the case of fluid dynamics, you know, you…”