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ORCIDNeha Mukund Kalibhat
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2020 – today
- 2024
[c6]Neha Mukund Kalibhat, Kanika Narang, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Measuring Self-Supervised Representation Quality for Downstream Classification Using Discriminative Features. AAAI 2024: 13031-13039- [i8]Warren R. Morningstar, Alex Bijamov, Chris Duvarney, Luke Friedman, Neha Mukund Kalibhat, Luyang Liu, Philip Andrew Mansfield, Renan A. Rojas-Gomez, Karan Singhal, Bradley Green, Sushant Prakash:
Augmentations vs Algorithms: What Works in Self-Supervised Learning. CoRR abs/2403.05726 (2024) - [i7]Neha Mukund Kalibhat, Priyatham Kattakinda, Arman Zarei, Nikita Seleznev, Samuel Sharpe, Senthil Kumar, Soheil Feizi:
Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning. CoRR abs/2405.16401 (2024) - 2023
- [c5]Neha Mukund Kalibhat, Samuel Sharpe, Jeremy Goodsitt, C. Bayan Bruss, Soheil Feizi:
Adapting Self-Supervised Representations to Multi-Domain Setups. BMVC 2023: 353-355 - [c4]Neha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Identifying Interpretable Subspaces in Image Representations. ICML 2023: 15623-15638 - [i6]Neha Mukund Kalibhat, Shweta Bhardwaj, C. Bayan Bruss, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Identifying Interpretable Subspaces in Image Representations. CoRR abs/2307.10504 (2023) - [i5]Neha Mukund Kalibhat, Samuel Sharpe, Jeremy Goodsitt, C. Bayan Bruss, Soheil Feizi:
Adapting Self-Supervised Representations to Multi-Domain Setups. CoRR abs/2309.03999 (2023) - [i4]Neha Mukund Kalibhat, Warren R. Morningstar, Alex Bijamov, Luyang Liu, Karan Singhal, Philip Andrew Mansfield:
Disentangling the Effects of Data Augmentation and Format Transform in Self-Supervised Learning of Image Representations. CoRR abs/2312.02205 (2023) - 2022
- [i3]Neha Mukund Kalibhat, Kanika Narang, Liang Tan, Hamed Firooz, Maziar Sanjabi, Soheil Feizi:
Understanding Failure Modes of Self-Supervised Learning. CoRR abs/2203.01881 (2022) - 2021
- [c3]Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi:
Winning Lottery Tickets in Deep Generative Models. AAAI 2021: 8038-8046 - [c2]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi
, Soheil Feizi:
Understanding Over-parameterization in Generative Adversarial Networks. ICLR 2021 - [i2]Yogesh Balaji, Mohammadmahdi Sajedi, Neha Mukund Kalibhat, Mucong Ding, Dominik Stöger, Mahdi Soltanolkotabi, Soheil Feizi:
Understanding Overparameterization in Generative Adversarial Networks. CoRR abs/2104.05605 (2021) - 2020
- [i1]Neha Mukund Kalibhat, Yogesh Balaji, Soheil Feizi:
Winning Lottery Tickets in Deep Generative Models. CoRR abs/2010.02350 (2020)
2010 – 2019
- 2017
- [c1]Neha Mukund Kalibhat, Shreya Varshini, Chid Kollengode, Dinkar Sitaram, Subramaniam Kalambur:
Software Troubleshooting Using Machine Learning. HiPC Workshops 2017: 3-10
Coauthor Index
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