120 citations · 213 across the 34 of their papers we have counts for
12 papers · 1 filter
STeP-Diff: Spatio-Temporal Physics-Informed Diffusion Models for Mobile Fine-Grained Pollution Forecasting
Nan Zhou, Weijie Hong, Huandong Wang +6
Fine-grained air pollution forecasting is crucial for urban management and the development of healthy buildings. Deploying portable sensors on mobile platforms such as cars and bus…
Predicting Human Mobility during Extreme Events via LLM-Enhanced Cross-City Learning
Yinzhou Tang, Huandong Wang, Xiaochen Fan +1
The vulnerability of cities has increased with urbanization and climate change, making it more important to predict human mobility during extreme events (e.g., extreme weather) for…
UniCO: Towards a Unified Model for Combinatorial Optimization Problems
Zefang Zong, Xiaochen Wei, Guozhen Zhang +3
Combinatorial Optimization (CO) encompasses a wide range of problems that arise in many real-world scenarios. While significant progress has been made in developing learning-based…
PhyxMamba: Chaotic System Reconstruction from Short Context Observations with Generative State-Space Models
Chang Liu, Bohao Zhao, Jingtao Ding +2
Understanding chaotic dynamics is a fundamental problem across scientific disciplines, including climate science, neuroscience, and fluid dynamics, yet direct experimentation and i…
Causality Enhanced Origin-Destination Flow Prediction in Data-Scarce Cities
Tao Feng, Yunke Zhang, Huandong Wang +1
Accurate origin-destination (OD) flow prediction is of great importance to developing cities, as it can contribute to optimize urban structures and layouts. However, with the commo…
EPR-GAIL: An EPR-Enhanced Hierarchical Imitation Learning Framework to Simulate Complex User Consumption Behaviors
Tao Feng, Yunke Zhang, Huandong Wang +1
User consumption behavior data, which records individuals' online spending history at various types of stores, has been widely used in various applications, such as store recommend…
One Fits All: General Mobility Trajectory Modeling via Masked Conditional Diffusion
Qingyue Long, Can Rong, Huandong Wang +1
Trajectory data play a crucial role in many applications, ranging from network optimization to urban planning. Existing studies on trajectory data are task-specific, and their appl…
PateGail: A Privacy-Preserving Mobility Trajectory Generator with Imitation Learning
Huandong Wang, Changzheng Gao, Yuchen Wu +3
Generating human mobility trajectories is of great importance to solve the lack of large-scale trajectory data in numerous applications, which is caused by privacy concerns. Howeve…
A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models
Wenjie Fu, Huandong Wang, Liyuan Zhang +3
Membership Inference Attack (MIA) identifies whether a record exists in a machine learning model's training set by querying the model. MIAs on the classic classification models hav…
Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network
Jinzhu Mao, Liu Cao, Chen Gao +4
Understanding and characterizing the vulnerability of urban infrastructures, which refers to the engineering facilities essential for the regular running of cities and that exist n…
Origin-Destination Network Generation via Gravity-Guided GAN
Can Rong, Huandong Wang, Yong Li
Origin-destination (OD) flow, which contains valuable population mobility information including direction and volume, is critical in many urban applications, such as urban planning…
Learning to Simulate Daily Activities via Modeling Dynamic Human Needs
Yuan Yuan, Huandong Wang, Jingtao Ding +2
Daily activity data that records individuals' various types of activities in daily life are widely used in many applications such as activity scheduling, activity recommendation, a…