Sravanti Addepalli

Orcid: 0000-0001-7238-4603

According to our database1, Sravanti Addepalli authored at least 20 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations.
CoRR, 2024

Leveraging Vision-Language Models for Improving Domain Generalization in Image Classification.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

2023
Distilling from Vision-Language Models for Improved OOD Generalization in Vision Tasks.
CoRR, 2023

Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Certified Adversarial Robustness Within Multiple Perturbation Bounds.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

RMLVQA: A Margin Loss Approach For Visual Question Answering with Language Biases.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022
Learning an Invertible Output Mapping Can Mitigate Simplicity Bias in Neural Networks.
CoRR, 2022

DAFT: Distilling Adversarially Fine-tuned Models for Better OOD Generalization.
CoRR, 2022

Efficient and Effective Augmentation Strategy for Adversarial Training.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scaling Adversarial Training to Large Perturbation Bounds.
Proceedings of the Computer Vision - ECCV 2022, 2022

Towards Efficient and Effective Self-supervised Learning of Visual Representations.
Proceedings of the Computer Vision - ECCV 2022, 2022

Towards Data-Free Model Stealing in a Hard Label Setting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021
Towards Efficient and Effective Adversarial Training.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Boosting Adversarial Robustness Using Feature Level Stochastic Smoothing.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Saliency-Driven Class Impressions For Feature Visualization Of Deep Neural Networks.
Proceedings of the IEEE International Conference on Image Processing, 2020

Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

DeGAN: Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2013


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