Bayesian Intermittent Demand Forecasting at NeurIPS 2016

Oldie but a goodie: A recording of Matthias Seeger’s presentation of “Bayesian Intermittent Demand Forecasting for Large Inventories” at NeurIPS 2016. The corresponding paper is a favorite of mine, but I only now stumbled over the presentation. It sparked an entire catalogue of work on time series forecasting by Amazon, and like few others called out the usefulness of sample paths.