52 citations · 81 across the 9 of their papers we have counts for
9 papers
2nd Place Solution for CVPR2024 E2E Challenge: End-to-End Autonomous Driving Using Vision Language Model
Zilong Guo, Yi Luo, Long Sha +4
End-to-end autonomous driving has drawn tremendous attention recently. Many works focus on using modular deep neural networks to construct the end-to-end archi-tecture. However, wh…
Knowledgebra: An Algebraic Learning Framework for Knowledge Graph
Tong Yang, Yifei Wang, Long Sha +2
Knowledge graph (KG) representation learning aims to encode entities and relations into dense continuous vector spaces such that knowledge contained in a dataset could be consisten…
Semi-supervised Dense Keypoints Using Unlabeled Multiview Images
Zhixuan Yu, Haozheng Yu, Long Sha +2
This paper presents a new end-to-end semi-supervised framework to learn a dense keypoint detector using unlabeled multiview images. A key challenge lies in finding the exact corres…
Variance Regularization for Accelerating Stochastic Optimization
Tong Yang, Long Sha, Pengyu Hong
While nowadays most gradient-based optimization methods focus on exploring the high-dimensional geometric features, the random error accumulated in a stochastic version of any algo…
A Deep Learning Approach for COVID-19 Trend Prediction
Tong Yang, Long Sha, Justin Li +1
In this work, we developed a deep learning model-based approach to forecast the spreading trend of SARS-CoV-2 in the United States. We implemented the designed model using the Unit…
NagE: Non-Abelian Group Embedding for Knowledge Graphs
Tong Yang, Long Sha, Pengyu Hong
We demonstrated the existence of a group algebraic structure hidden in relational knowledge embedding problems, which suggests that a group-based embedding framework is essential f…