KD-PINN: Accelerating PDE Solutions with Knowledge Distillation for Real-time Applications

This research explores a novel application of knowledge distillation within Physics-Informed Neural Networks (PINNs) to improve the speed of solving partial differential equations. The focus on ultra-low latency highlights its potential for real-time applications, which could revolutionize various fields.

• •KD-PINN leverages knowledge distillation to accelerate PINNs.
• •The research aims for ultra-low latency, enabling real-time PDE solving.
• •This could have significant impact on fields requiring fast PDE solutions.