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user retention forecasting

topic1 events
papersTODAY 04:00 UTC

PPDL framework combines physical priors with deep learning for user retention forecasting

Researchers present PPDL, a framework for predicting channel-level user retention ratios in multi-channel paid user acquisition. The method integrates physical priors with deep learning to capture the sharp early churn typical of retention curves. Accurate early forecasts are intended to help marketers allocate advertising budgets more effectively.

forecasting/deep-learning/advertising/research