3 papers
cs.LG2026
Time-Series Foundation Models That Understand Data Revisions
Taimoor Ahmad
Historical observations are not always fixed: statistical agencies revise previously published values as new evidence arrives. Forecasting from a contemporary download can therefor…
cs.CR2026
Differentially Private and Fairness-Audited Score Diffusion for Irregular Longitudinal Health Records
Taimoor Ahmad
Sharing irregular longitudinal health records can accelerate model development, yet synthetic releases may leak participation, distort temporal dependence, suppress rare events, or…
cs.LG2026
Calibration-First Cross-Cohort Multimodal Temporal Learning for Transferable Asthma-Risk Forecasting
Taimoor Ahmad
Asthma deterioration forecasting must remain reli- able when patient populations, sensor ecosystems, and available modalities change across cohorts. Existing models commonly optimi…