253 citations · 338 across the 16 of their papers we have counts for
16 papers
PULSE: Generative Phase Evolution for Non-Stationary Time Series Forecasting
Yangyou Liu, Zezhi Shao, Xinyu Chen +3
Time series forecasting under non-stationarity faces a fundamental tension between capturing stable representations and adapting to distribution shifts. Existing methods implicitly…
Implicit Action Chunking for Smooth Continuous Control
Bosun Liang, Shuo Pei, Zirui Chen +5
Reinforcement learning often produces high-frequency oscillatory control signals that undermine the safety and stability required for physical deployment. Explicit action chunking…
Enhancing Representation Learning for Periodic Time Series with Floss: A Frequency Domain Regularization Approach
Chunwei Yang, Xiaoxu Chen, Lijun Sun +2
Time series analysis is a fundamental task in various application domains, and deep learning approaches have demonstrated remarkable performance in this area. However, many real-wo…
Spatial-temporal traffic modeling with a fusion graph reconstructed by tensor decomposition
Qin Li, Xuan Yang, Yong Wang +2
Accurate spatial-temporal traffic flow forecasting is essential for helping traffic managers to take control measures and drivers to choose the optimal travel routes. Recently, gra…
Explainable and Safe Reinforcement Learning for Autonomous Air Mobility
Lei Wang, Hongyu Yang, Yi Lin +2
Increasing traffic demands, higher levels of automation, and communication enhancements provide novel design opportunities for future air traffic controllers (ATCs). This article p…
Spatiotemporal Propagation Learning for Network-Wide Flight Delay Prediction
Yuankai Wu, Hongyu Yang, Yi Lin +1
Demystifying the delay propagation mechanisms among multiple airports is fundamental to precise and interpretable delay prediction, which is crucial during decision-making for all…
Spatial Aggregation and Temporal Convolution Networks for Real-time Kriging
Yuankai Wu, Dingyi Zhuang, Mengying Lei +2
Spatiotemporal kriging is an important application in spatiotemporal data analysis, aiming to recover/interpolate signals for unsampled/unobserved locations based on observed signa…
Individual Mobility Prediction via Attentive Marked Temporal Point Processes
Yuankai Wu, Zhanhong Cheng, Lijun Sun
Individual mobility prediction is an essential task for transportation demand management and traffic system operation. There exist a large body of works on modeling location sequen…
Low-Rank Hankel Tensor Completion for Traffic Speed Estimation
Xudong Wang, Yuankai Wu, Dingyi Zhuang +1
This paper studies the traffic state estimation (TSE) problem using sparse observations from mobile sensors. Most existing TSE methods either rely on well-defined physical traffic…
Efficient Connected and Automated Driving System with Multi-agent Graph Reinforcement Learning
Tianyu Shi, Jiawei Wang, Yuankai Wu +2
Connected and automated vehicles (CAVs) have attracted more and more attention recently. The fast actuation time allows them having the potential to promote the efficiency and safe…
Inductive Graph Neural Networks for Spatiotemporal Kriging
Yuankai Wu, Dingyi Zhuang, Aurelie Labbe +1
Time series forecasting and spatiotemporal kriging are the two most important tasks in spatiotemporal data analysis. Recent research on graph neural networks has made substantial p…
Non-recurrent Traffic Congestion Detection with a Coupled Scalable Bayesian Robust Tensor Factorization Model
Qin Li, Huachun Tan, Xizhu Jiang +2
Non-recurrent traffic congestion (NRTC) usually brings unexpected delays to commuters. Hence, it is critical to accurately detect and recognize the NRTC in a real-time manner. The…
ES-CTC: A Deep Neuroevolution Model for Cooperative Intelligent Freeway Traffic Control
Yuankai Wu, Huachun Tan, Zhuxi Jiang +1
Cooperative intelligent freeway traffic control is an important application in intelligent transportation systems, which is expected to improve the mobility of freeway networks. In…
Efficient Motion Planning for Automated Lane Change based on Imitation Learning and Mixed-Integer Optimization
Chenyang Xi, Tianyu Shi, Yuankai Wu +1
Intelligent motion planning is one of the core components in automated vehicles, which has received extensive interests. Traditional motion planning methods suffer from several dra…
Differential Variable Speed Limits Control for Freeway Recurrent Bottlenecks via Deep Reinforcement learning
Yuankai Wu, Huachun Tan, Bin Ran
Variable speed limits (VSL) control is a flexible way to improve traffic condition,increase safety and reduce emission. There is an emerging trend of using reinforcement learning t…
Short-term traffic flow forecasting with spatial-temporal correlation in a hybrid deep learning framework
Yuankai Wu, Huachun Tan
Deep learning approaches have reached a celebrity status in artificial intelligence field, its success have mostly relied on Convolutional Networks (CNN) and Recurrent Networks. By…