A comprehensive survey on deep graph representation learning
Graph representation learning aims to effectively encode high-dimensional sparse graph-
structured data into low-dimensional dense vectors, which is a fundamental task that has …
structured data into low-dimensional dense vectors, which is a fundamental task that has …
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 …
Difftraj: Generating gps trajectory with diffusion probabilistic model
Pervasive integration of GPS-enabled devices and data acquisition technologies has led to
an exponential increase in GPS trajectory data, fostering advancements in spatial-temporal …
an exponential increase in GPS trajectory data, fostering advancements in spatial-temporal …
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 …
Controltraj: Controllable trajectory generation with topology-constrained diffusion model
Generating trajectory data is among promising solutions to addressing privacy concerns,
collection costs, and proprietary restrictions usually associated with human mobility …
collection costs, and proprietary restrictions usually associated with human mobility …
Spatio-temporal diffusion point processes
Spatio-temporal point process (STPP) is a stochastic collection of events accompanied with
time and space. Due to computational complexities, existing solutions for STPPs …
time and space. Due to computational complexities, existing solutions for STPPs …
Practical synthetic human trajectories generation based on variational point processes
Human trajectories, reflecting people's travel patterns and the range of activities, are crucial
for the applications like urban planning and epidemic control. However, the real-world …
for the applications like urban planning and epidemic control. However, the real-world …
Large language models as urban residents: An llm agent framework for personal mobility generation
This paper introduces a novel approach using Large Language Models (LLMs) integrated
into an agent framework for flexible and effective personal mobility generation. LLMs …
into an agent framework for flexible and effective personal mobility generation. LLMs …
Diff-rntraj: A structure-aware diffusion model for road network-constrained trajectory generation
Trajectory data is essential for various applications. However, publicly available trajectory
datasets remain limited in scale due to privacy concerns, which hinders the development of …
datasets remain limited in scale due to privacy concerns, which hinders the development of …
Urban generative intelligence (ugi): A foundational platform for agents in embodied city environment
Urban environments, characterized by their complex, multi-layered networks encompassing
physical, social, economic, and environmental dimensions, face significant challenges in the …
physical, social, economic, and environmental dimensions, face significant challenges in the …