no code implementations • CVPR 2023 • Aditay Tripathi, Rishubh Singh, Anirban Chakraborty, Pradeep Shenoy
We show that our augmentations significantly improve classification accuracy and robustness measures on a range of datasets and neural architectures.
no code implementations • 14 Nov 2022 • Aditay Tripathi, Rishubh Singh, Anirban Chakraborty, Pradeep Shenoy
We also obtain gains of up to 28% and 8. 5% on natural adversarial and out-of-distribution datasets like ImageNet-A (for ViT-B) and ImageNet-R (for ViT-S), respectively.
1 code implementation • CVPR 2022 • Rishubh Singh, Pranav Gupta, Pradeep Shenoy, Ravikiran Sarvadevabhatla
Our framework involves independent dense prediction of object category and part attributes which increases scalability and reduces task complexity compared to the monolithic label space counterpart.
1 code implementation • ACL 2020 • Gantavya Bhatt, Hritik Bansal, Rishubh Singh, Sumeet Agarwal
Long short-term memory (LSTM) networks and their variants are capable of encapsulating long-range dependencies, which is evident from their performance on a variety of linguistic tasks.
Ranked #35 on Language Modelling on WikiText-103 (Validation perplexity metric)