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Balaji Krishnamurthy
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Publications
- 2023
- [c52]Surgan Jandial, Yash Khasbage, Arghya Pal, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
RetroKD : Leveraging Past States for Regularizing Targets in Teacher-Student Learning. COMAD/CODS 2023: 10-18 - [i58]Tarun Ram Menta, Surgan Jandial, Akash Patil, Vimal KB, Saketh Bachu, Balaji Krishnamurthy, Vineeth N. Balasubramanian, Chirag Agarwal, Mausoom Sarkar:
Towards Estimating Transferability using Hard Subsets. CoRR abs/2301.06928 (2023) - 2022
- [c39]Surgan Jandial, Yash Khasbage, Arghya Pal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Distilling the Undistillable: Learning from a Nasty Teacher. ECCV (13) 2022: 587-603 - [c34]Puneet Mangla, Nupur Kumari, Mayank Singh, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
Data InStance Prior (DISP) in Generative Adversarial Networks. WACV 2022: 3471-3481 - [i44]Vedant Singh, Surgan Jandial, Ayush Chopra, Siddharth Ramesh, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models. CoRR abs/2205.03859 (2022) - [i42]Puneet Mangla, Shivam Chandhok, Milan Aggarwal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
INDIGO: Intrinsic Multimodality for Domain Generalization. CoRR abs/2206.05912 (2022) - [i37]Surgan Jandial, Yash Khasbage, Arghya Pal, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Distilling the Undistillable: Learning from a Nasty Teacher. CoRR abs/2210.11728 (2022) - 2020
- [c26]Mayank Singh, Nupur Kumari, Puneet Mangla, Abhishek Sinha, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Attributional Robustness Training Using Input-Gradient Spatial Alignment. ECCV (27) 2020: 515-533 - [c20]Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. KDD 2020: 1123-1131 - [c17]Puneet Mangla, Mayank Singh, Abhishek Sinha, Nupur Kumari, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Charting the Right Manifold: Manifold Mixup for Few-shot Learning. WACV 2020: 2207-2216 - [i20]Surgan Jandial, Ayush Chopra, Mausoom Sarkar, Piyush Gupta, Balaji Krishnamurthy, Vineeth Balasubramanian:
Retrospective Loss: Looking Back to Improve Training of Deep Neural Networks. CoRR abs/2006.13593 (2020) - [i14]Puneet Mangla, Nupur Kumari, Mayank Singh, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Data Instance Prior for Transfer Learning in GANs. CoRR abs/2012.04256 (2020) - 2019
- [c11]Nupur Kumari, Mayank Singh, Abhishek Sinha, Harshitha Machiraju, Balaji Krishnamurthy, Vineeth N. Balasubramanian:
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models. IJCAI 2019: 2779-2785 - [i13]Abhishek Sinha, Mayank Singh, Nupur Kumari, Balaji Krishnamurthy, Harshitha Machiraju, Vineeth N. Balasubramanian:
Harnessing the Vulnerability of Latent Layers in Adversarially Trained Models. CoRR abs/1905.05186 (2019) - [i12]Puneet Mangla, Mayank Singh, Abhishek Sinha, Nupur Kumari, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
Charting the Right Manifold: Manifold Mixup for Few-shot Learning. CoRR abs/1907.12087 (2019) - [i9]Mayank Singh, Nupur Kumari, Puneet Mangla, Abhishek Sinha, Vineeth N. Balasubramanian, Balaji Krishnamurthy:
On the Benefits of Attributional Robustness. CoRR abs/1911.13073 (2019)
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