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An interdisciplinary survey on origin-destination flows modeling: Theory and techniques
Origin-destination (OD) flow modeling is an extensively researched subject across multiple
disciplines, such as the investigation of travel demand in transportation and spatial …
disciplines, such as the investigation of travel demand in transportation and spatial …
Towards urban general intelligence: A review and outlook of urban foundation models
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 …
Deep learning for cross-domain data fusion in urban computing: Taxonomy, advances, and outlook
As cities continue to burgeon, Urban Computing emerges as a pivotal discipline for
sustainable development by harnessing the power of cross-domain data fusion from diverse …
sustainable development by harnessing the power of cross-domain data fusion from diverse …
Urbankg: An urban knowledge graph system
Every day, our living city produces a tremendous amount of spatial-temporal data, involved
with multiple sources from the individual scale to the city scale. Undoubtedly, such massive …
with multiple sources from the individual scale to the city scale. Undoubtedly, such massive …
Urbanclip: Learning text-enhanced urban region profiling with contrastive language-image pretraining from the web
Urban region profiling from web-sourced data is of utmost importance for urban computing.
We are witnessing a blossom of LLMs for various fields, especially in multi-modal data …
We are witnessing a blossom of LLMs for various fields, especially in multi-modal data …
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 …
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 …
Urban region embedding via multi-view contrastive prediction
Recently, learning urban region representations utilizing multi-modal data (information
views) has become increasingly popular, for deep understanding of the distributions of …
views) has become increasingly popular, for deep understanding of the distributions of …
Geolocation representation from large language models are generic enhancers for spatio-temporal learning
In the geospatial domain, universal representation models are significantly less prevalent
than their extensive use in natural language processing and computer vision. This …
than their extensive use in natural language processing and computer vision. This …
Spatial heterophily aware graph neural networks
Graph Neural Networks (GNNs) have been broadly applied in many urban applications
upon formulating a city as an urban graph whose nodes are urban objects like regions or …
upon formulating a city as an urban graph whose nodes are urban objects like regions or …