| Guided adversarial attack for evaluating and enhancing adversarial defenses G Sriramanan, S Addepalli, A Baburaj Advances in Neural Information Processing Systems 33, 20297-20308, 2020 | 114 | 2020 |
| Towards data-free model stealing in a hard label setting S Sanyal, S Addepalli, RV Babu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 112 | 2022 |
| Towards efficient and effective adversarial training G Sriramanan, S Addepalli, A Baburaj Advances in Neural Information Processing Systems 34, 11821-11833, 2021 | 84 | 2021 |
| Efficient and effective augmentation strategy for adversarial training S Addepalli, S Jain Advances in Neural Information Processing Systems 35, 1488-1501, 2022 | 59 | 2022 |
| Scaling adversarial training to large perturbation bounds S Addepalli, S Jain, G Sriramanan, R Venkatesh Babu European Conference on Computer Vision, 301-316, 2022 | 56* | 2022 |
| Towards achieving adversarial robustness by enforcing feature consistency across bit planes S Addepalli, V BS, A Baburaj, G Sriramanan, RV Babu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 50 | 2020 |
| Degan: Data-enriching gan for retrieving representative samples from a trained classifier S Addepalli, GK Nayak, A Chakraborty, VB Radhakrishnan Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 3130-3137, 2020 | 48 | 2020 |
| On chip ZQ calibration resistor trimming S Addepalli, S Yadala US Patent 9,563,213, 2017 | 25 | 2017 |
| Rmlvqa: A margin loss approach for visual question answering with language biases A Basu, S Addepalli, RV Babu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 23 | 2023 |
| Dart: Diversify-aggregate-repeat training improves generalization of neural networks S Jain, S Addepalli, PK Sahu, P Dey, RV Babu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 23 | 2023 |
| Search for impedance calibration H Miwa, S Addepalli, S Yadala US Patent 9,531,382, 2016 | 20 | 2016 |
| Duty cycle and skew correction for output signals generated in source synchronous systems S Addepalli, RA Madpur, S Yadala US Patent 10,367,493, 2019 | 16 | 2019 |
| Towards efficient and effective self-supervised learning of visual representations S Addepalli, K Bhogale, P Dey, RV Babu European Conference on Computer Vision, 523-538, 2022 | 12 | 2022 |
| Boosting adversarial robustness using feature level stochastic smoothing S Addepalli, S Jain, G Sriramanan, RV Babu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 10 | 2021 |
| Efficient Peak Current Management In A Multi-Die Stack S Addepalli, S Yadala US Patent App. 15/099,496, 2017 | 10 | 2017 |
| Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification S Addepalli, AR Asokan, L Sharma, RV Babu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 7 | 2024 |
| Feature reconstruction from outputs can mitigate simplicity bias in neural networks S Addepalli, A Nasery, VB Radhakrishnan, P Netrapalli, P Jain The Eleventh International Conference on Learning Representations, 2022 | 7 | 2022 |
| Certified Adversarial Robustness Within Multiple Perturbation Bounds S Nandi, S Addepalli, H Rangwani, RV Babu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 4 | 2023 |
| Learning an invertible output mapping can mitigate simplicity bias in neural networks S Addepalli, A Nasery, RV Babu, P Netrapalli, P Jain arXiv preprint arXiv:2210.01360, 2022 | 4 | 2022 |
| Duty cycle and skew correction for output signals generated in source synchronous systems S Addepalli, RA Madpur, S Yadala US Patent 10,361,690, 2019 | 4 | 2019 |
R. Venkatesh BabuCDS, Indian Institute of Science, Bangalore, IndiaEmail verificata su iisc.ac.in
