2 citations · 2 across the 6 of their papers we have counts for
8 papers
Envisioning global urban development with satellite imagery and generative AI
Kailai Sun, Yuebing Liang, Mingyi He +5
Urban development has been a defining force in human history, shaping cities for centuries. However, past studies mostly analyze such development as predictive tasks, failing to re…
Data-Driven Discovery of Mobility Periodicity for Understanding Urban Systems
Xinyu Chen, Qi Wang, Yunhan Zheng +3
Human mobility regularity is crucial for understanding urban dynamics and informing decision-making processes. This study first quantifies the periodicity in complex human mobility…
Interpretable Time Series Autoregression for Periodicity Quantification
Xinyu Chen, Vassilis Digalakis, Lijun Ding +2
Time series autoregression (AR) is a classical tool for modeling auto-correlations and periodic structures in real-world systems. We revisit this model from an interpretable machin…
Generative AI for Urban Design: A Stepwise Approach Integrating Human Expertise with Multimodal Diffusion Models
Mingyi He, Yuebing Liang, Shenhao Wang +5
Urban design is a multifaceted process that demands careful consideration of site-specific constraints and collaboration among diverse professionals and stakeholders. The advent of…
Generative AI for Urban Planning: Synthesizing Satellite Imagery via Diffusion Models
Qingyi Wang, Yuebing Liang, Yunhan Zheng +3
Generative AI offers new opportunities for automating urban planning by creating site-specific urban layouts and enabling flexible design exploration. However, existing approaches…
Reimagining Urban Science: Scaling Causal Inference with Large Language Models
Yutong Xia, Ao Qu, Yunhan Zheng +8
Urban causal research is essential for understanding the complex, dynamic processes that shape cities and for informing evidence-based policies. However, current practices are ofte…