1 code implementation • 28 Feb 2024 • Han Guo, Ramtin Hosseini, Ruiyi Zhang, Sai Ashish Somayajula, Ranak Roy Chowdhury, Rajesh K. Gupta, Pengtao Xie
Masked Autoencoder (MAE) is a notable method for self-supervised pretraining in visual representation learning.
1 code implementation • 2 Feb 2024 • Xiyuan Zhang, Ranak Roy Chowdhury, Rajesh K. Gupta, Jingbo Shang
Large Language Models (LLMs) have seen significant use in domains such as natural language processing and computer vision.
no code implementations • 12 Nov 2023 • Xiyuan Zhang, Xiaohan Fu, Diyan Teng, chengyu dong, Keerthivasan Vijayakumar, Jiayun Zhang, Ranak Roy Chowdhury, Junsheng Han, Dezhi Hong, Rashmi Kulkarni, Jingbo Shang, Rajesh Gupta
By obviating the need for ground truth clean data, our method offers a practical denoising solution for real-world applications.
no code implementations • 24 Mar 2023 • Xiyuan Zhang, Ranak Roy Chowdhury, Jingbo Shang, Rajesh Gupta, Dezhi Hong
We note that augmentation designed for forecasting requires diversity as well as coherence with the original temporal dynamics.
no code implementations • 1 Jan 2023 • Xiyuan Zhang, Ranak Roy Chowdhury, Jiayun Zhang, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang
In this paper, we propose SHARE, a HAR framework that takes into account shared structures of label names for different activities.