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Found 5 papers, 1 papers with code
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 analyses.
Enhancing Traffic Prediction with Learnable Filter Module
Our approach focuses on enhancing the quality of the input data for traffic prediction models, which is a critical yet often overlooked aspect in the field.
Meta Attentive Graph Convolutional Recurrent Network for Traffic Forecasting
Firstly, most approaches are primarily designed to model the local shared patterns, which makes them insufficient to capture the specific patterns associated with each node globally.
DiffTraj: Generating GPS Trajectory with Diffusion Probabilistic Model
In this work, we propose a spatial-temporal diffusion probabilistic model for trajectory generation (DiffTraj).
Adaptive Modeling of Uncertainties for Traffic Forecasting
We evaluated QuanTraffic by applying it to five representative DNN models for traffic forecasting across seven public datasets.
