Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale.
Matthias W. SeegerSyama Sundar RangapuramYuyang WangDavid SalinasJan GasthausTim JanuschowskiValentin FlunkertPublished in: CoRR (2017)
Keyphrases
- bayesian inference
- probabilistic model
- state space
- variational inference
- gibbs sampler
- bayesian models
- prior information
- particle filter
- demand forecasting
- hyperparameters
- model selection
- expectation propagation
- markov chain monte carlo
- random fields
- genetic algorithm
- expert systems
- historical data
- graphical models
- management system
- prior knowledge
- support vector
- decision trees
- learning algorithm