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Found 4 papers, 3 papers with code
Do Sentence Transformers Learn Quasi-Geospatial Concepts from General Text?
Sentence transformers are language models designed to perform semantic search.
Time Series Supplier Allocation via Deep Black-Litterman Model
Time Series Supplier Allocation (TSSA) poses a complex NP-hard challenge, aimed at refining future order dispatching strategies to satisfy order demands with maximum supply efficiency fully.
Spatiotemporal Graph Neural Networks with Uncertainty Quantification for Traffic Incident Risk Prediction
This model strategically employs a compound model from the Tweedie family, as a Poisson distribution to model risk frequency and a Gamma distribution to account for incident severity.
Uncertainty Quantification via Spatial-Temporal Tweedie Model for Zero-inflated and Long-tail Travel Demand Prediction
Understanding Origin-Destination (O-D) travel demand is crucial for transportation management.
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