1 code implementation • ICCV 2023 • Aaditya Singh, Kartik Sarangmath, Prithvijit Chattopadhyay, Judy Hoffman
Robustness to natural distribution shifts has seen remarkable progress thanks to recent pre-training strategies combined with better fine-tuning methods.
1 code implementation • 16 Jun 2022 • Viraj Prabhu, Sriram Yenamandra, Aaditya Singh, Judy Hoffman
Inspired by the design of recent SSL approaches based on learning from partial image inputs generated via masking or cropping -- either by learning to predict the missing pixels, or learning representational invariances to such augmentations -- we propose PACMAC, a simple two-stage adaptation algorithm for self-supervised ViTs.
4 code implementations • 22 Apr 2022 • Stephanie C. Y. Chan, Adam Santoro, Andrew K. Lampinen, Jane X. Wang, Aaditya Singh, Pierre H. Richemond, Jay McClelland, Felix Hill
In further experiments, we found that naturalistic data distributions were only able to elicit in-context learning in transformers, and not in recurrent models.
1 code implementation • 13 May 2021 • Aaditya Singh, Shreeshail Hingane, Xinyu Gong, Zhangyang Wang
We demonstrate that plugging SAFIN into the base network of another state-of-the-art method results in enhanced stylization.
1 code implementation • 2 Mar 2021 • Aaditya Singh, Shreeshail Hingane, Saim Wani, Ashutosh Modi
The task of Emotion-Cause Pair Extraction (ECPE) aims to extract all potential clause-pairs of emotions and their corresponding causes in a document.