26 citations · 42 across the 5 of their papers we have counts for
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cs.LG2024★ 1 cited
Expected Grad-CAM: Towards gradient faithfulness
Vincenzo Buono, Peyman Sheikholharam Mashhadi, Mahmoud Rahat +2
Although input-gradients techniques have evolved to mitigate and tackle the challenges associated with gradients, modern gradient-weighted CAM approaches still rely on vanilla grad…
cs.LG2024★ 26 cited
Rolling the dice for better deep learning performance: A study of randomness techniques in deep neural networks
Mohammed Ghaith Altarabichi, Sławomir Nowaczyk, Sepideh Pashami +2
This paper investigates how various randomization techniques impact Deep Neural Networks (DNNs). Randomization, like weight noise and dropout, aids in reducing overfitting and enha…