Transferable Graph Structure Learning for Graph-based Traffic Forecasting Across Cities.
Yilun JinKai ChenQiang YangPublished in: KDD (2023)
Keyphrases
- structure learning
- graphical models
- bayesian networks
- graph theoretic
- bayesian network structure learning
- traffic congestion
- parameter learning
- graph structure
- conditional independence
- parameter estimation
- transfer learning
- markov logic networks
- graph theory
- random walk
- directed graph
- traffic flow
- sample size
- structure learning algorithm
- markov networks
- random variables
- network structure
- machine learning
- conditional random fields
- least squares
- probability distribution
- higher order