73 citations · 137 across the 17 of their papers we have counts for
6 papers · 1 filter
Spatio-Temporal Scene-Graph Embedding for Autonomous Vehicle Collision Prediction
Arnav V. Malawade, Shih-Yuan Yu, Brandon Hsu +3
In autonomous vehicles (AVs), early warning systems rely on collision prediction to ensure occupant safety. However, state-of-the-art methods using deep convolutional networks eith…
Graph Learning for Cognitive Digital Twins in Manufacturing Systems
Trier Mortlock, Deepan Muthirayan, Shih-Yuan Yu +2
Future manufacturing requires complex systems that connect simulation platforms and virtualization with physical data from industrial processes. Digital twins incorporate a physica…
roadscene2vec: A Tool for Extracting and Embedding Road Scene-Graphs
Arnav Vaibhav Malawade, Shih-Yuan Yu, Brandon Hsu +3
Recently, road scene-graph representations used in conjunction with graph learning techniques have been shown to outperform state-of-the-art deep learning techniques in tasks inclu…
HW2VEC: A Graph Learning Tool for Automating Hardware Security
Shih-Yuan Yu, Rozhin Yasaei, Qingrong Zhou +2
The time-to-market pressure and continuous growing complexity of hardware designs have promoted the globalization of the Integrated Circuit (IC) supply chain. However, such globali…
Robo-Advising: Enhancing Investment with Inverse Optimization and Deep Reinforcement Learning
Haoran Wang, Shi Yu
Machine Learning (ML) has been embraced as a powerful tool by the financial industry, with notable applications spreading in various domains including investment management. In thi…
Few-Shot Conversational Dense Retrieval
Shi Yu, Zhenghao Liu, Chenyan Xiong +2
Dense retrieval (DR) has the potential to resolve the query understanding challenge in conversational search by matching in the learned embedding space. However, this adaptation is…