| Zero-Shot Knowledge Distillation in Deep Networks GK Nayak, KR Mopuri, V Shaj, RV Babu, A Chakraborty International Conference on Machine Learning (ICML), 4743-4751, 2019 | 199 | 2019 |
| 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 | 27 | 2020 |
| Classification of normal versus malignant cells in B-ALL white blood cancer microscopic images A Honnalgere, G Nayak ISBI 2019 C-NMC Challenge: Classification in Cancer Cell Imaging: Select …, 2019 | 26 | 2019 |
| Development and comparative analysis of fuzzy inference systems for predicting customer buying behavior GK Nayak, SJ Narayanan, I Paramasivam International Journal of Engineering and Technology 5 (5), 4093-4108, 2013 | 19 | 2013 |
| Effectiveness of arbitrary transfer sets for data-free knowledge distillation GK Nayak, KR Mopuri, A Chakraborty Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2021 | 16 | 2021 |
| DAD: Data-free adversarial defense at test time GK Nayak, R Rawal, A Chakraborty Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 5 | 2022 |
| Mining Data Impressions From Deep Models as Substitute for the Unavailable Training Data GK Nayak, KR Mopuri, S Jain, A Chakraborty IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (11), 8465 …, 2021 | 4 | 2021 |
| Holistic approach to measure sample-level adversarial vulnerability and its utility in building trustworthy systems GK Nayak, R Rawal, R Lal, H Patil, A Chakraborty Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 3 | 2022 |
| Beyond Classification: Knowledge Distillation using Multi-Object Impressions GK Nayak, M Keswani, S Seshadri, A Chakraborty The British Machine Vision Conference (BMVC), 2021 | 2 | 2021 |
| Efficient person re-identification in videos using sequence lazy greedy determinantal point process (slgdpp) GK Nayak, U Shreemali, RV Babu, A Chakraborty 2019 IEEE International Conference on Image Processing (ICIP), 4569-4573, 2019 | 2 | 2019 |
| Incremental Learning for Animal Pose Estimation using RBF k-DPP GK Nayak, H Shah, A Chakraborty The British Machine Vision Conference (BMVC), 2021 | 1 | 2021 |
| Fusion of Deep and Non-Deep Methods for Fast Super-Resolution of Satellite Images GK Nayak, S Jain, RV Babu, A Chakraborty 2020 IEEE Sixth International Conference on Multimedia Big Data (BigMM), 267-271, 2020 | 1 | 2020 |
| DAD++: Improved Data-free Test Time Adversarial Defense GK Nayak, I Khatri, S Randive, R Rawal, A Chakraborty arXiv preprint arXiv:2309.05132, 2023 | | 2023 |
| DISBELIEVE: Distance Between Client Models is Very Essential for Effective Local Model Poisoning Attacks I Joshi, P Upadhya, GK Nayak, P Schüffler, N Navab arXiv preprint arXiv:2308.07387, 2023 | | 2023 |
| Federated Learning on Heterogeneous Data via Adaptive Self-Distillation M Yashwanth, G Nayak, A Singh, Y Singh, A Chakraborty arXiv preprint arXiv:2305.19600, 2023 | | 2023 |
| Data-efficient Deep Learning Algorithms for Computer Vision Applications GK Nayak | | 2023 |
| DE-CROP: Data-efficient Certified Robustness for Pretrained Classifiers GK Nayak, R Rawal, A Chakraborty Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | | 2023 |
| Query Efficient Cross-Dataset Transferable Black-Box Attack on Action Recognition R Gupta, N Akhtar, GK Nayak, A Mian, M Shah arXiv preprint arXiv:2211.13171, 2022 | | 2022 |
| Data-free Defense of Black Box Models Against Adversarial Attacks GK Nayak, I Khatri, S Randive, R Rawal, A Chakraborty arXiv preprint arXiv:2211.01579, 2022 | | 2022 |
| Robust Few-shot Learning Without Using any Adversarial Samples GK Nayak, R Rawal, I Khatri, A Chakraborty arXiv preprint arXiv:2211.01598, 2022 | | 2022 |
Anirban ChakrabortyIndian Institute of Science, BangaloreVerified email at iisc.ac.in
