Associate Professor, Wuhan University
1 paper at NeurIPS 2025
AdaptGrad proposed in this paper aims to reduces noise in gradient-based model explanations by controlling out-of-range sampling behavior, outperforming existing techniques like SmoothGrad in noise reduction and visualization quality.
