no code implementations • 26 Apr 2022 • Xiaolong He, Youngsoo Choi, William D. Fries, Jon Belof, Jiun-Shyan Chen
To maximize and accelerate the exploration of the parameter space for the optimal model performance, an adaptive greedy sampling algorithm integrated with a physics-informed residual-based error indicator and random-subset evaluation is introduced to search for the optimal training samples on the fly.
