Sravanti Addepalli

According to our database, Sravanti Addepalli authored at least 18 papers between 2013 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

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

Sravanti Addepalli, Ashish Ramayee Asokan, Lakshay Sharma, R. Venkatesh Babu

CoRR, 2023

Feature Reconstruction From Outputs Can Mitigate Simplicity Bias in Neural Networks.

Sravanti Addepalli, Anshul Nasery, Venkatesh Babu Radhakrishnan, Praneeth Netrapalli, Prateek Jain

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Certified Adversarial Robustness Within Multiple Perturbation Bounds.

Soumalya Nandi, Sravanti Addepalli, Harsh Rangwani, R. Venkatesh Babu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks.

Samyak Jain, Sravanti Addepalli, Pawan Kumar Sahu, Priyam Dey, R. Venkatesh Babu

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.

Abhipsa Basu, Sravanti Addepalli, R. Venkatesh Babu

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.

Sravanti Addepalli, Anshul Nasery, R. Venkatesh Babu, Praneeth Netrapalli, Prateek Jain

CoRR, 2022

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

Anshul Nasery, Sravanti Addepalli, Praneeth Netrapalli, Prateek Jain

CoRR, 2022

Efficient and Effective Augmentation Strategy for Adversarial Training.

Sravanti Addepalli, Samyak Jain, Venkatesh Babu R.

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.

Sravanti Addepalli, Samyak Jain, Gaurang Sriramanan, R. Venkatesh Babu

Proceedings of the Computer Vision - ECCV 2022, 2022

Towards Efficient and Effective Self-supervised Learning of Visual Representations.

Sravanti Addepalli, Kaushal Bhogale, Priyam Dey, R. Venkatesh Babu

Proceedings of the Computer Vision - ECCV 2022, 2022

Towards Data-Free Model Stealing in a Hard Label Setting.

Sunandini Sanyal, Sravanti Addepalli, R. Venkatesh Babu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

2021

Towards Efficient and Effective Adversarial Training.

Gaurang Sriramanan, Sravanti Addepalli, Arya Baburaj, Venkatesh Babu R.

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.

Sravanti Addepalli, Samyak Jain, Gaurang Sriramanan, R. Venkatesh Babu

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2021

2020

Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses.

Gaurang Sriramanan, Sravanti Addepalli, Arya Baburaj, Venkatesh Babu R.

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.

Sravanti Addepalli, Dipesh Tamboli, R. Venkatesh Babu, Biplab Banerjee

Proceedings of the IEEE International Conference on Image Processing, 2020

Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes.

Sravanti Addepalli, Vivek B. S., Arya Baburaj, Gaurang Sriramanan, R. Venkatesh Babu

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.

Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, Venkatesh Babu Radhakrishnan

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2013

A 130.7mm² 2-layer 32Gb ReRAM memory device in 24nm technology.

Tz-Yi Liu, Tian Hong Yan, Roy Scheuerlein, Yingchang Chen, Jeffrey KoonYee Lee, Gopinath Balakrishnan, Gordon Yee, Henry Zhang, Alex Yap, Jingwen Ouyang, Takahiko Sasaki, Sravanti Addepalli, Ali Al-Shamma, Chin-Yu Chen, Mayank Gupta, Greg Hilton, Saurabh Joshi, Achal Kathuria, Vincent Lai, Deep Masiwal, Masahide Matsumoto, Anurag Nigam, Anil Pai, Jayesh Pakhale, Chang Hua Siau, Xiaoxia Wu, Ronald Yin, Liping Peng, Jang Yong Kang, Sharon Huynh, Huijuan Wang, Nicolas Nagel, Yoichiro Tanaka, Masaaki Higashitani, Tim Minvielle, Chandu Gorla, Takayuki Tsukamoto, Takeshi Yamaguchi, Mutsumi Okajima, Takayuki Okamura, Satoru Takase, Takahiko Hara, Hirofumi Inoue, Luca Fasoli, Mehrdad Mofidi, Ritu Shrivastava, Khandker Quader

Proceedings of the 2013 IEEE International Solid-State Circuits Conference, 2013