4 papers
Understanding the Theoretical Foundations of Deep Neural Networks through Differential Equations
Hongjue Zhao, Yizhuo Chen, Yuchen Wang +4
Deep neural networks (DNNs) have achieved remarkable empirical success, yet the absence of a principled theoretical foundation continues to hinder their systematic development. In…
A Generalizable Physics-guided Causal Model for Trajectory Prediction in Autonomous Driving
Zhenyu Zong, Yuchen Wang, Haohong Lin +2
Trajectory prediction for traffic agents is critical for safe autonomous driving. However, achieving effective zero-shot generalization in previously unseen domains remains a signi…
A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments
Yuchen Wang, Hongjue Zhao, Haohong Lin +3
This work aims to address the problem of long-term dynamic forecasting in complex environments where data are noisy and irregularly sampled. While recent studies have introduced so…
TrafficKAN-GCN: Graph Convolutional-based Kolmogorov-Arnold Network for Traffic Flow Optimization
Jiayi Zhang, Yiming Zhang, Yuan Zheng +5
Urban traffic optimization is critical for improving transportation efficiency and alleviating congestion, particularly in large-scale dynamic networks. Traditional methods, such a…