Full Professor, Nanjing University
2 papers at NeurIPS 2025
We propose Curriculum Abductive Learning (C-ABL), a method that explicitly leverages structural properties of domain knowledge bases to improve training efficiency, stability and reasoning accuracy in ABL.
We propose a dual-driven (data and knowledge) approach for symbolic PDE discovery that exhibits superior performance in terms of noise robustness and hyperparameter stability.