3 citations · 3 across the 3 of their papers we have counts for
3 papers
DAD++: Improved Data-free Test Time Adversarial Defense
Gaurav Kumar Nayak, Inder Khatri, Shubham Randive +2
With the increasing deployment of deep neural networks in safety-critical applications such as self-driving cars, medical imaging, anomaly detection, etc., adversarial robustness h…
What Happens During Finetuning of Vision Transformers: An Invariance Based Investigation
Gabriele Merlin, Vedant Nanda, Ruchit Rawal +1
The pretrain-finetune paradigm usually improves downstream performance over training a model from scratch on the same task, becoming commonplace across many areas of machine learni…
DAD: Data-free Adversarial Defense at Test Time
Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
Deep models are highly susceptible to adversarial attacks. Such attacks are carefully crafted imperceptible noises that can fool the network and can cause severe consequences when…