AutoBNN: Probabilistic time series forecasting with compositional bayesian neural networks | AI 资讯 | 云织星·工具台

Posted by Urs Köster, Software Engineer, Google Research Time series problems are ubiquitous, from forecasting weather and traffic patterns to understanding economic trends. Bayesian approaches start with an assumption about the data's patterns (prior probability), collecting evidence (e.g.

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