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Sravanti Addepalli
Sravanti Addepalli
PhD Student, Indian Institute of Science, Bangalore
Geverifieerd e-mailadres voor iisc.ac.in
Titel
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Geciteerd door
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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
652020
Towards efficient and effective adversarial training
G Sriramanan, S Addepalli, A Baburaj
Advances in Neural Information Processing Systems 34, 11821-11833, 2021
412021
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
382020
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
372022
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
302020
Scaling adversarial training to large perturbation bounds
S Addepalli, S Jain, G Sriramanan, R Venkatesh Babu
European Conference on Computer Vision, 301-316, 2022
26*2022
On chip ZQ calibration resistor trimming
S Addepalli, S Yadala
US Patent 9,563,213, 2017
202017
Search for impedance calibration
H Miwa, S Addepalli, S Yadala
US Patent 9,531,382, 2016
182016
Efficient and effective augmentation strategy for adversarial training
S Addepalli, S Jain
Advances in Neural Information Processing Systems 35, 1488-1501, 2022
152022
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
102019
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
92021
Efficient Peak Current Management In A Multi-Die Stack
S Addepalli, S Yadala
US Patent App. 15/099,496, 2017
92017
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
42023
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
42022
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
42022
Saliency-driven class impressions for feature visualization of deep neural networks
S Addepalli, D Tamboli, RV Babu, B Banerjee
2020 IEEE International Conference on Image Processing (ICIP), 1936-1940, 2020
32020
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
32019
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
22023
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
12022
DAFT: Distilling Adversarially Fine-tuned Models for Better OOD Generalization
A Nasery, S Addepalli, P Netrapalli, P Jain
arXiv preprint arXiv:2208.09139, 2022
12022
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Artikelen 1–20