2 citations · 5 across the 11 of their papers we have counts for
10 papers
Human-instructed Deep Hierarchical Generative Learning for Automated Urban Planning
Dongjie Wang, Lingfei Wu, Denghui Zhang +3
The essential task of urban planning is to generate the optimal land-use configuration of a target area. However, traditional urban planning is time-consuming and labor-intensive.…
Automated Urban Planning aware Spatial Hierarchies and Human Instructions
Dongjie Wang, Kunpeng Liu, Yanyong Huang +3
Traditional urban planning demands urban experts to spend considerable time and effort producing an optimal urban plan under many architectural constraints. The remarkable imaginat…
Group-wise Reinforcement Feature Generation for Optimal and Explainable Representation Space Reconstruction
Dongjie Wang, Yanjie Fu, Kunpeng Liu +2
Representation (feature) space is an environment where data points are vectorized, distances are computed, patterns are characterized, and geometric structures are embedded. Extrac…
Reinforced Imitative Graph Learning for Mobile User Profiling
Dongjie Wang, Pengyang Wang, Yanjie Fu +3
Mobile user profiling refers to the efforts of extracting users' characteristics from mobile activities. In order to capture the dynamic varying of user characteristics for generat…
Deep Human-guided Conditional Variational Generative Modeling for Automated Urban Planning
Dongjie Wang, Kunpeng Liu, Pauline Johnson +3
Urban planning designs land-use configurations and can benefit building livable, sustainable, safe communities. Inspired by image generation, deep urban planning aims to leverage d…
Efficient Reinforced Feature Selection via Early Stopping Traverse Strategy
Kunpeng Liu, Pengfei Wang, Dongjie Wang +3
In this paper, we propose a single-agent Monte Carlo based reinforced feature selection (MCRFS) method, as well as two efficiency improvement strategies, i.e., early stopping (ES)…