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cs.LG2024
GeoPro-Net: Learning Interpretable Spatiotemporal Prediction Models through Statistically-Guided Geo-Prototyping
Bang An, Xun Zhou, Zirui Zhou +3
The problem of forecasting spatiotemporal events such as crimes and accidents is crucial to public safety and city management. Besides accuracy, interpretability is also a key requ…
cs.LG2023
AutoFed: Heterogeneity-Aware Federated Multimodal Learning for Robust Autonomous Driving
Tianyue Zheng, Ang Li, Zhe Chen +2
Object detection with on-board sensors (e.g., lidar, radar, and camera) play a crucial role in autonomous driving (AD), and these sensors complement each other in modalities. While…