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Sandesh Kamath
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2020 – today
- 2024
- [c5]Sandesh Kamath, Sankalp Mittal, Amit Deshpande, Vineeth N. Balasubramanian:
Rethinking Robustness of Model Attributions. AAAI 2024: 2688-2696 - [c4]Sandesh Kamath, Albin Soutif-Cormerais, Joost van de Weijer, Bogdan Raducanu:
The Expanding Scope of the Stability Gap: Unveiling its Presence in Joint Incremental Learning of Homogeneous Tasks. CVPR Workshops 2024: 4182-4186 - [c3]Dipam Goswami, Albin Soutif-Cormerais, Yuyang Liu, Sandesh Kamath, Bartlomiej Twardowski, Joost van de Weijer:
Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning. CVPR 2024: 28525-28534 - [i8]Dipam Goswami, Albin Soutif-Cormerais, Yuyang Liu, Sandesh Kamath, Bartlomiej Twardowski, Joost van de Weijer:
Resurrecting Old Classes with New Data for Exemplar-Free Continual Learning. CoRR abs/2405.19074 (2024) - [i7]Sandesh Kamath, Albin Soutif-Cormerais, Joost van de Weijer, Bogdan Raducanu:
The Expanding Scope of the Stability Gap: Unveiling its Presence in Joint Incremental Learning of Homogeneous Tasks. CoRR abs/2406.05114 (2024) - 2023
- [i6]Sandesh Kamath, Sankalp Mittal, Amit Deshpande, Vineeth N. Balasubramanian:
Rethinking Robustness of Model Attributions. CoRR abs/2312.10534 (2023) - 2022
- [c2]Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam, Vineeth N. Balasubramanian:
Universalization of Any Adversarial Attack using Very Few Test Examples. COMAD/CODS 2022: 72-80 - [i5]Amlan Jyoti, Karthik Balaji Ganesh, Manoj Gayala, Nandita Lakshmi Tunuguntla, Sandesh Kamath, Vineeth N. Balasubramanian:
On the Robustness of Explanations of Deep Neural Network Models: A Survey. CoRR abs/2211.04780 (2022) - 2021
- [c1]Sandesh Kamath, Amit Deshpande, Subrahmanyam Kambhampati Venkata, Vineeth N. Balasubramanian:
Can we have it all? On the Trade-off between Spatial and Adversarial Robustness of Neural Networks. NeurIPS 2021: 27462-27474 - 2020
- [i4]Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam:
Invariance vs. Robustness of Neural Networks. CoRR abs/2002.11318 (2020) - [i3]Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam:
Universalization of any adversarial attack using very few test examples. CoRR abs/2005.08632 (2020) - [i2]Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam:
On Universalized Adversarial and Invariant Perturbations. CoRR abs/2006.04449 (2020) - [i1]Sandesh Kamath, Amit Deshpande, K. V. Subrahmanyam:
How do SGD hyperparameters in natural training affect adversarial robustness? CoRR abs/2006.11604 (2020)
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