FOLLY
发表于 2025-3-25 05:18:23
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未开化
发表于 2025-3-25 10:02:00
POI-Based Traffic Generation via Supervised Contrastive Learning on Reconstructed Graph termed as ., which combines POI data and road network data to generate the distribution of traffic flows. Our model has two novel modules: a graph reconstruction module and a POI supervised contrastive module. The graph reconstruction module includes a .-NN graph builder and a .-NN graph aggregator
议程
发表于 2025-3-25 11:45:04
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水槽
发表于 2025-3-25 17:14:40
https://doi.org/10.1007/978-3-642-72814-3or calculation pruning. We conduct extensive experiments using three diverse datasets from different domains (ranging from taxis to trucks to pedestrians), which verifies the efficiency of our method.
吹牛者
发表于 2025-3-25 23:42:59
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新奇
发表于 2025-3-26 01:41:05
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oxidize
发表于 2025-3-26 06:09:14
0302-9743 lications, DASFAA 2024, held in Gifu, Japan, in July 2024...The total of 147 full papers, along with 85 short papers, presented together in this seven-volume set was carefully reviewed and selected from 722 submissions...Additionally, 14 industrial papers, 18 demo papers and 6 tutorials are included
staging
发表于 2025-3-26 09:17:48
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符合规定
发表于 2025-3-26 13:54:16
Artificial Neural Networks in Excel,en, . learns time-aware encodings of these trajectories by a newly proposed time-aware recurrent unit. Moreover, a popularity-weighted attention mechanism is proposed to complete the missing locations. Extensive experiments on four datasets show that . outperforms competitive baselines with up to 25% relative improvements.
Regurgitation
发表于 2025-3-26 20:20:28
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