Sen Li

Achieving 96.06% accuracy in laser welding penetration prediction with only 200 labeled images could revolutionize quality assurance in industrial applications.

Achieving over 80% accuracy in cross-process welding penetration prediction could revolutionize intelligent monitoring across diverse welding systems.

WeldMamba achieves a remarkable 74.63% mIoU in predicting weld pool dynamics, setting a new benchmark for real-time welding applications.

Achieve state-of-the-art MARL performance by having agents reach a consensus in latent space before acting, effectively transforming the multi-agent problem into a hierarchical single-agent one.