#machine learning
Feb 2026
How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting
This work decomposes infections into trend, seasonal, and residual components and uses these signals to drive continuous-time latent dynamics while jointly forecasting and inferring time-varying transmission, recovery, and immunity-loss rates.
Yiqi Su, R. Lee, J. Cui et al.
· arXiv.org · 1 citation