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Vivek Ramanujan
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2020 – today
- 2024
- [i13]Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna:
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. CoRR abs/2406.05184 (2024) - 2023
- [c12]Matthew Wallingford, Aditya Kusupati, Alex Fang, Vivek Ramanujan, Aniruddha Kembhavi, Roozbeh Mottaghi, Ali Farhadi:
Neural Radiance Field Codebooks. ICLR 2023 - [c11]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander J. Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. NeurIPS 2023 - [c10]Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ali Farhadi, Ludwig Schmidt:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. NeurIPS 2023 - [c9]Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi:
Neural Priming for Sample-Efficient Adaptation. NeurIPS 2023 - [i12]Matthew Wallingford, Aditya Kusupati, Alex Fang, Vivek Ramanujan, Aniruddha Kembhavi, Roozbeh Mottaghi, Ali Farhadi:
Neural Radiance Field Codebooks. CoRR abs/2301.04101 (2023) - [i11]Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt:
DataComp: In search of the next generation of multimodal datasets. CoRR abs/2304.14108 (2023) - [i10]Matthew Wallingford, Vivek Ramanujan, Alex Fang, Aditya Kusupati, Roozbeh Mottaghi, Aniruddha Kembhavi, Ludwig Schmidt, Ali Farhadi:
Neural Priming for Sample-Efficient Adaptation. CoRR abs/2306.10191 (2023) - [i9]Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ludwig Schmidt, Ali Farhadi:
On the Connection between Pre-training Data Diversity and Fine-tuning Robustness. CoRR abs/2307.12532 (2023) - 2022
- [c8]Vivek Ramanujan, Pavan Kumar Anasosalu Vasu, Ali Farhadi, Oncel Tuzel, Hadi Pouransari:
Forward Compatible Training for Large-Scale Embedding Retrieval Systems. CVPR 2022: 19364-19373 - [c7]Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder, Kaifeng Chen, Sham M. Kakade, Prateek Jain, Ali Farhadi:
Matryoshka Representation Learning. NeurIPS 2022 - [i8]Aditya Kusupati, Gantavya Bhatt, Aniket Rege, Matthew Wallingford, Aditya Sinha, Vivek Ramanujan, William Howard-Snyder
, Kaifeng Chen, Sham M. Kakade, Prateek Jain, Ali Farhadi:
Matryoshka Representations for Adaptive Deployment. CoRR abs/2205.13147 (2022) - 2021
- [c6]William Merrill, Vivek Ramanujan, Yoav Goldberg, Roy Schwartz, Noah A. Smith:
Effects of Parameter Norm Growth During Transformer Training: Inductive Bias from Gradient Descent. EMNLP (1) 2021: 1766-1781 - [c5]Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi:
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. NeurIPS 2021: 23900-23913 - [i7]Aditya Kusupati, Matthew Wallingford, Vivek Ramanujan, Raghav Somani, Jae Sung Park, Krishna Pillutla, Prateek Jain, Sham M. Kakade, Ali Farhadi:
LLC: Accurate, Multi-purpose Learnt Low-dimensional Binary Codes. CoRR abs/2106.01487 (2021) - [i6]Vivek Ramanujan, Pavan Kumar Anasosalu Vasu, Ali Farhadi, Oncel Tuzel, Hadi Pouransari:
Forward Compatible Training for Representation Learning. CoRR abs/2112.02805 (2021) - 2020
- [c4]Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi, Ali Farhadi, Mohammad Rastegari:
What's Hidden in a Randomly Weighted Neural Network? CVPR 2020: 11890-11899 - [c3]Aditya Kusupati, Vivek Ramanujan, Raghav Somani, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. ICML 2020: 5544-5555 - [c2]Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi:
Supermasks in Superposition. NeurIPS 2020 - [i5]Aditya Kusupati, Vivek Ramanujan, Raghav Somani
, Mitchell Wortsman, Prateek Jain, Sham M. Kakade, Ali Farhadi:
Soft Threshold Weight Reparameterization for Learnable Sparsity. CoRR abs/2002.03231 (2020) - [i4]Mitchell Wortsman, Vivek Ramanujan, Rosanne Liu, Aniruddha Kembhavi, Mohammad Rastegari, Jason Yosinski, Ali Farhadi:
Supermasks in Superposition. CoRR abs/2006.14769 (2020) - [i3]William Merrill, Vivek Ramanujan, Yoav Goldberg, Roy Schwartz, Noah A. Smith:
Parameter Norm Growth During Training of Transformers. CoRR abs/2010.09697 (2020)
2010 – 2019
- 2019
- [i2]Vivek Ramanujan, Mitchell Wortsman, Aniruddha Kembhavi, Ali Farhadi, Mohammad Rastegari:
What's Hidden in a Randomly Weighted Neural Network? CoRR abs/1911.13299 (2019) - 2018
- [c1]Aaron Gokaslan
, Vivek Ramanujan
, Daniel Ritchie
, Kwang In Kim, James Tompkin
:
Improving Shape Deformation in Unsupervised Image-to-Image Translation. ECCV (12) 2018: 662-678 - [i1]Aaron Gokaslan, Vivek Ramanujan, Daniel Ritchie, Kwang In Kim, James Tompkin:
Improving Shape Deformation in Unsupervised Image-to-Image Translation. CoRR abs/1808.04325 (2018)
Coauthor Index
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last updated on 2024-07-25 20:26 CEST by the dblp team
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