9 papers · 1 filter
ADV-0: Closed-Loop Min-Max Adversarial Training for Long-Tail Robustness in Autonomous Driving
Tong Nie, Yihong Tang, Junlin He +5
Deploying autonomous driving systems requires robustness against long-tail scenarios that are rare but safety-critical. While adversarial training offers a promising solution, exis…
Predicting Large-scale Urban Network Dynamics with Energy-informed Graph Neural Diffusion
Tong Nie, Jian Sun, Wei Ma
Networked urban systems facilitate the flow of people, resources, and services, and are essential for economic and social interactions. These systems often involve complex processe…
Joint Estimation and Prediction of City-wide Delivery Demand: A Large Language Model Empowered Graph-based Learning Approach
Tong Nie, Junlin He, Yuewen Mei +4
The proliferation of e-commerce and urbanization has significantly intensified delivery operations in urban areas, boosting the volume and complexity of delivery demand. Data-drive…
Collaborative Imputation of Urban Time Series through Cross-city Meta-learning
Tong Nie, Wei Ma, Jian Sun +2
Urban time series, such as mobility flows, energy consumption, and pollution records, encapsulate complex urban dynamics and structures. However, data collection in each city is im…
Contextualizing MLP-Mixers Spatiotemporally for Urban Data Forecast at Scale
Tong Nie, Guoyang Qin, Lijun Sun +3
Spatiotemporal traffic data (STTD) displays complex correlational structures. Extensive advanced techniques have been designed to capture these structures for effective forecasting…
Spatiotemporal Implicit Neural Representation as a Generalized Traffic Data Learner
Tong Nie, Guoyang Qin, Wei Ma +1
Spatiotemporal Traffic Data (STTD) measures the complex dynamical behaviors of the multiscale transportation system. Existing methods aim to reconstruct STTD using low-dimensional…