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epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery.

, , , , , , , and . KDD, page 5847-5848. ACM, (2023)

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Performative Time-Series Forecasting., , and . CoRR, (2023)When Rigidity Hurts: Soft Consistency Regularization for Probabilistic Hierarchical Time Series Forecasting., , , , and . KDD, page 1057-1072. ACM, (2023)Back2Future: Leveraging Backfill Dynamics for Improving Real-time Predictions in Future., , and . CoRR, (2021)Data-Centric Epidemic Forecasting: A Survey., , , , , , and . CoRR, (2022)Differentiable Agent-based Epidemiology., , , , , and . CoRR, (2022)CAMul: Calibrated and Accurate Multi-view Time-Series Forecasting., , , , and . WWW, page 3174-3185. ACM, (2022)epiDAMIK 6.0: The 6th International Workshop on Epidemiology meets Data Mining and Knowledge Discovery., , , , , , , and . KDD, page 5847-5848. ACM, (2023)When in Doubt: Neural Non-Parametric Uncertainty Quantification for Epidemic Forecasting., , , , and . NeurIPS, page 19796-19807. (2021)DeepCOVID: An Operational Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting., , , , , , , and . AAAI, page 15393-15400. AAAI Press, (2021)Mapping Network States using Connectivity Queries., , , , , and . IEEE BigData, page 778-787. IEEE, (2020)