Urban foundation models: A survey
Machine learning techniques are now integral to the advancement of intelligent urban
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
services, playing a crucial role in elevating the efficiency, sustainability, and livability of …
UUKG: unified urban knowledge graph dataset for urban spatiotemporal prediction
Abstract Accurate Urban SpatioTemporal Prediction (USTP) is of great importance to the
development and operation of the smart city. As an emerging building block, multi-sourced …
development and operation of the smart city. As an emerging building block, multi-sourced …
Kill two birds with one stone: A multi-view multi-adversarial learning approach for joint air quality and weather prediction
Accurate and timely air quality and weather predictions are of great importance to urban
governance and human livelihood. Though many efforts have been made for air quality or …
governance and human livelihood. Though many efforts have been made for air quality or …
Interpretable cascading mixture-of-experts for urban traffic congestion prediction
Rapid urbanization has significantly escalated traffic congestion, underscoring the need for
advanced congestion prediction services to bolster intelligent transportation systems. As one …
advanced congestion prediction services to bolster intelligent transportation systems. As one …
COMET: NFT Price Prediction with Wallet Profiling
As the non-fungible token (NFT) market flourishes, price prediction emerges as a pivotal
direction for investors gaining valuable insight to maximize returns. However, existing works …
direction for investors gaining valuable insight to maximize returns. However, existing works …
RLCharge: Imitative multi-agent spatiotemporal reinforcement learning for electric vehicle charging station recommendation
Electric Vehicle (EV) has become a preferable choice in the modern transportation system
due to its environmental and energy sustainability. However, in many large cities, EV drivers …
due to its environmental and energy sustainability. However, in many large cities, EV drivers …
A contextual master-slave framework on urban region graph for urban village detection
Urban villages (UVs) refer to the underdeveloped informal settlement falling behind the
rapid urbanization in a city. Since there are high levels of social inequality and social risks in …
rapid urbanization in a city. Since there are high levels of social inequality and social risks in …
Uncertainty-aware probabilistic travel time prediction for on-demand ride-hailing at didi
Travel Time Estimation (TTE) aims to accurately forecast the expected trip duration from an
origin to a destination. As one of the world's largest ride-hailing platforms, DiDi answers …
origin to a destination. As one of the world's largest ride-hailing platforms, DiDi answers …
Irregular Traffic Time Series Forecasting Based on Asynchronous Spatio-Temporal Graph Convolutional Networks
Accurate traffic forecasting is crucial for the development of Intelligent Transportation
Systems (ITS), playing a pivotal role in modern urban traffic management. Traditional …
Systems (ITS), playing a pivotal role in modern urban traffic management. Traditional …
St-rap: A spatio-temporal framework for real estate appraisal
In this paper, we introduce ST-RAP, a novel Spatio-Temporal framework for Real estate
APpraisal. ST-RAP employs a hierarchical architecture with a heterogeneous graph neural …
APpraisal. ST-RAP employs a hierarchical architecture with a heterogeneous graph neural …