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Nayak, GK and Khatri, I and Rawal, R and Chakraborty, A (2024) Data-free Defense of Black Box Models Against Adversarial Attacks. In: 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2024, 16 June 2024through 22 June 2024, Seattle, pp. 254-263.
Nayak, GK and Rawal, R and Chakraborty, A (2023) DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. In: 23rd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2023, 3 - 7 January 2023, Waikoloa, pp. 4611-4620.
Nayak, GK and Rawal, R and Lal, R and Patil, H and Chakraborty, A (2022) Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. In: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022, 19 - 20 June 2022, New Orleans, pp. 4331-4340.
Nayak, GK and Rawal, R and Chakraborty, A (2022) DAD: Data-free Adversarial Defense at Test Time. In: 22nd IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2022, 4 - 8 January 2022, Waikoloa, pp. 3788-3797.
