Using Grad-CAM with ResNets, this study probes how deep learning classifies anomalous diffusion from raw trajectories. The method reveals trajectory segments and multiscale features driving predictions, improving interpretability and robustness to measurement noise.
- Jaeyong Bae
- Yongjoo Baek
- Hawoong Jeong
