Gaurav Kumar Nayak

46 papers A* 4A 7B 1Journal 28Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	SIDiffAgent: Self-Improving Diffusion Agent. CoRR Shivank Garg, Ayush Singh, Gaurav Kumar Nayak
2025	J	`jnl`	DAD++: Improved data-free test time adversarial defense. Neurocomputing Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty
2025	A	`conf`	DLCR: A Generative Data Expansion Framework via Diffusion for Clothes-Changing Person Re-Id. WACV Nyle Siddiqui, Florinel-Alin Croitoru, Gaurav Kumar Nayak, Radu Tudor Ionescu, Mubarak Shah
2025	J	`jnl`	DeepSeaVision: Enhanced Detection and Classification of Underwater Species. IEEE Access G. Joshita Reddy, Keerthika Reddy, Sai Ruthvik Athota, Swathi Jamjala Narayanan, Boominathan Perumal, Gaurav Kumar Nayak
2025	J	`jnl`	MGD CoRR Jeffrey A. Chan-Santiago, Praveen Tirupattur, Gaurav Kumar Nayak, Gaowen Liu, Mubarak Shah
2025	A*	`conf`	MGD3 : Mode-Guided Dataset Distillation using Diffusion Models. ICML Jeffrey A. Chan-Santiago, Praveen Tirupattur, Gaurav Kumar Nayak, Gaowen Liu, Mubarak Shah
2025	J	`jnl`	Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning. CoRR M. Yashwanth, Gaurav Kumar Nayak, Harsh Rangwani, Arya Singh, R. Venkatesh Babu, Anirban Chakraborty
2025	—	`conf`	Open-DeBias: Toward Mitigating Open-Set Bias in Language Models. EMNLP (Findings) Arti Rani, Shweta Singh, Nihar Ranjan Sahoo, Gaurav Kumar Nayak
2025	J	`jnl`	Open-DeBias: Toward Mitigating Open-Set Bias in Language Models. CoRR Arti Rani, Shweta Singh, Nihar Ranjan Sahoo, Gaurav Kumar Nayak
2025	J	`jnl`	Robust Few-Shot Learning Without Using Any Adversarial Samples. IEEE Trans. Neural Networks Learn. Syst. Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri, Anirban Chakraborty
2024	J	`jnl`	Adaptive Self-Distillation for Minimizing Client Drift in Heterogeneous Federated Learning. Trans. Mach. Learn. Res. M. Yashwanth, Gaurav Kumar Nayak, Arya Singh, Yogesh Simmhan, Anirban Chakraborty
2024	—	`conf`	CityGuessr: City-Level Video Geo-Localization on a Global Scale. ECCV (63) Parth Parag Kulkarni, Gaurav Kumar Nayak, Mubarak Shah
2024	J	`jnl`	CityGuessr: City-Level Video Geo-Localization on a Global Scale. CoRR Parth Parag Kulkarni, Gaurav Kumar Nayak, Mubarak Shah
2024	J	`jnl`	DLCR: A Generative Data Expansion Framework via Diffusion for Clothes-Changing Person Re-ID. CoRR Nyle Siddiqui, Florinel-Alin Croitoru, Gaurav Kumar Nayak, Radu Tudor Ionescu, Mubarak Shah
2024	—	`conf`	Data-free Defense of Black Box Models Against Adversarial Attacks. CVPR Workshops Gaurav Kumar Nayak, Inder Khatri, Ruchit Rawal, Anirban Chakraborty
2024	A	`conf`	Minimizing Layerwise Activation Norm Improves Generalization in Federated Learning. WACV M. Yashwanth, Gaurav Kumar Nayak, Harsh Rangwani, Arya Singh, R. Venkatesh Babu, Anirban Chakraborty
2023	J	`jnl`	DAD++: Improved Data-free Test Time Adversarial Defense. CoRR Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty
2023	A	`conf`	DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. WACV Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
2023	—	`conf`	DISBELIEVE: Distance Between Client Models Is Very Essential for Effective Local Model Poisoning Attacks. ISIC/Care-AI/MedAGI/DeCaF@MICCAI Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter J. Schüffler, Nassir Navab
2023	J	`jnl`	DISBELIEVE: Distance Between Client Models is Very Essential for Effective Local Model Poisoning Attacks. CoRR Indu Joshi, Priyank Upadhya, Gaurav Kumar Nayak, Peter J. Schüffler, Nassir Navab
2023	J	`jnl`	Federated Learning on Heterogeneous Data via Adaptive Self-Distillation. CoRR M. Yashwanth, Gaurav Kumar Nayak, Arya Singh, Yogesh Singh, Anirban Chakraborty
2023	A*	`conf`	GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. NeurIPS Vicente Vivanco Cepeda, Gaurav Kumar Nayak, Mubarak Shah
2023	J	`jnl`	GeoCLIP: Clip-Inspired Alignment between Locations and Images for Effective Worldwide Geo-localization. CoRR Vicente Vivanco Cepeda, Gaurav Kumar Nayak, Mubarak Shah
2022	A	`conf`	DAD: Data-free Adversarial Defense at Test Time. WACV Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
2022	J	`jnl`	DAD: Data-free Adversarial Defense at Test Time. CoRR Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
2022	J	`jnl`	DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers. CoRR Gaurav Kumar Nayak, Ruchit Rawal, Anirban Chakraborty
2022	J	`jnl`	Data-free Defense of Black Box Models Against Adversarial Attacks. CoRR Gaurav Kumar Nayak, Inder Khatri, Shubham Randive, Ruchit Rawal, Anirban Chakraborty
2022	—	`conf`	Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. CVPR Workshops Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal, Himanshu Patil, Anirban Chakraborty
2022	J	`jnl`	Holistic Approach to Measure Sample-level Adversarial Vulnerability and its Utility in Building Trustworthy Systems. CoRR Gaurav Kumar Nayak, Ruchit Rawal, Rohit Lal, Himanshu Patil, Anirban Chakraborty
2022	J	`jnl`	Mining Data Impressions From Deep Models as Substitute for the Unavailable Training Data. IEEE Trans. Pattern Anal. Mach. Intell. Gaurav Kumar Nayak, Konda Reddy Mopuri, Saksham Jain, Anirban Chakraborty
2022	J	`jnl`	Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition. CoRR Rohit Gupta, Naveed Akhtar, Gaurav Kumar Nayak, Ajmal Mian, Mubarak Shah
2022	J	`jnl`	Robust Few-shot Learning Without Using any Adversarial Samples. CoRR Gaurav Kumar Nayak, Ruchit Rawal, Inder Khatri, Anirban Chakraborty
2021	A	`conf`	Beyond Classification: Knowledge Distillation using Multi-Object Impressions. BMVC Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri, Anirban Chakraborty
2021	J	`jnl`	Beyond Classification: Knowledge Distillation using Multi-Object Impressions. CoRR Gaurav Kumar Nayak, Monish Keswani, Sharan Seshadri, Anirban Chakraborty
2021	J	`jnl`	Data Impressions: Mining Deep Models to Extract Samples for Data-free Applications. CoRR Gaurav Kumar Nayak, Konda Reddy Mopuri, Saksham Jain, Anirban Chakraborty
2021	A	`conf`	Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation. WACV Gaurav Kumar Nayak, Konda Reddy Mopuri, Anirban Chakraborty
2021	A	`conf`	Incremental Learning for Animal Pose Estimation using RBF k-DPP. BMVC Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty
2021	J	`jnl`	Incremental Learning for Animal Pose Estimation using RBF k-DPP. CoRR Gaurav Kumar Nayak, Het Shah, Anirban Chakraborty
2020	A*	`conf`	DeGAN: Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier. AAAI Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, Venkatesh Babu Radhakrishnan
2020	J	`jnl`	Effectiveness of Arbitrary Transfer Sets for Data-free Knowledge Distillation. CoRR Gaurav Kumar Nayak, Konda Reddy Mopuri, Anirban Chakraborty
2020	—	`conf`	Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images. BigMM Gaurav Kumar Nayak, Saksham Jain, R. Venkatesh Babu, Anirban Chakraborty
2020	J	`jnl`	Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images. CoRR Gaurav Kumar Nayak, Saksham Jain, R. Venkatesh Babu, Anirban Chakraborty
2019	J	`jnl`	DeGAN : Data-Enriching GAN for Retrieving Representative Samples from a Trained Classifier. CoRR Sravanti Addepalli, Gaurav Kumar Nayak, Anirban Chakraborty, R. Venkatesh Babu
2019	B	`conf`	Efficient Person Re-Identification in Videos Using Sequence Lazy Greedy Determinantal Point Process (SLGDPP). ICIP Gaurav Kumar Nayak, Utkarsh Shreemali, R. Venkatesh Babu, Anirban Chakraborty
2019	A*	`conf`	Zero-Shot Knowledge Distillation in Deep Networks. ICML Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, Venkatesh Babu Radhakrishnan, Anirban Chakraborty
2019	J	`jnl`	Zero-Shot Knowledge Distillation in Deep Networks. CoRR Gaurav Kumar Nayak, Konda Reddy Mopuri, Vaisakh Shaj, R. Venkatesh Babu, Anirban Chakraborty