Transfer Learning using 66 Diseases for Disease Forecasting Applications
Fuente:
arXiv
Saved in:
| Main Authors: | Beesley, Lauren J, Murph, Alexander C, Osthus, Dave, Castro, Lauren A |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Mapping Incidence and Prevalence Peak Data for SIR Forecasting Applications
by: Murph, Alexander C., et al.
Published: (2024)
by: Murph, Alexander C., et al.
Published: (2024)
Leveraging Synthetic and Genetic Data to Improve Epidemic Forecasting
by: Osthus, Dave, et al.
Published: (2026)
by: Osthus, Dave, et al.
Published: (2026)
Code for the publication "Beyond Equal Weights: A Disease-agnostic Approach to Ensemble Learning for Infectious Disease Forecasting"
by: Murph, Alexander C., et al.
Published: (2025)
by: Murph, Alexander C., et al.
Published: (2025)
EpiFFORMA: Disease-Agnostic Ensemble Weighting for Forecasting Emerging Epidemic Time Series without Historical Data
by: Murph, Alexander C., et al.
Published: (2025)
by: Murph, Alexander C., et al.
Published: (2025)
Bayesian Statistical Inversion for High-Dimensional Computer Model Output and Spatially Distributed Counts
by: Barnett, Steven D., et al.
Published: (2025)
by: Barnett, Steven D., et al.
Published: (2025)
Sensitivity Analysis in the Presence of Intrinsic Stochasticity for Discrete Fracture Network Simulations
by: Murph, Alexander C., et al.
Published: (2023)
by: Murph, Alexander C., et al.
Published: (2023)
MMformer with Adaptive Transferable Attention: Advancing Multivariate Time Series Forecasting for Environmental Applications
by: Xin, Ning, et al.
Published: (2025)
by: Xin, Ning, et al.
Published: (2025)
Intelligent Diagnosis of Alzheimer's Disease Based on Machine Learning
by: Li, Mingyang, et al.
Published: (2024)
by: Li, Mingyang, et al.
Published: (2024)
User Engagement in Mobile Health Applications
by: Olaniyi, Babaniyi Yusuf, et al.
Published: (2022)
by: Olaniyi, Babaniyi Yusuf, et al.
Published: (2022)
Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study
by: Liu, Xueqing, et al.
Published: (2023)
by: Liu, Xueqing, et al.
Published: (2023)
Forecasting Medium-Horizon Alzheimer's Disease Progression: Residual Gap-Aware Transformers for 24-Month CDR-SB Change from ADNI Clinical and Biomarker Histories
by: Tong, Ran, et al.
Published: (2026)
by: Tong, Ran, et al.
Published: (2026)
Data-driven Calibration Sample Selection and Forecast Combination in Electricity Price Forecasting: An Application of the ARHNN Method
by: Serafin, Tomasz, et al.
Published: (2025)
by: Serafin, Tomasz, et al.
Published: (2025)
Neural Networks for Extreme Quantile Regression with an Application to Forecasting of Flood Risk
by: Pasche, Olivier C., et al.
Published: (2022)
by: Pasche, Olivier C., et al.
Published: (2022)
Federated Learning for Financial Forecasting
by: Noseda, Manuel, et al.
Published: (2025)
by: Noseda, Manuel, et al.
Published: (2025)
A More Realistic Evaluation of Cross-Frequency Transfer Learning and Foundation Forecasting Models
by: Olivares, Kin G., et al.
Published: (2025)
by: Olivares, Kin G., et al.
Published: (2025)
Adaptive Bayesian Very Short-Term Wind Power Forecasting Based on the Generalised Logit Transformation
by: Shen, Tao, et al.
Published: (2025)
by: Shen, Tao, et al.
Published: (2025)
Monitoring Machine Learning Forecasts for Platform Data Streams
by: Rombouts, Jeroen, et al.
Published: (2024)
by: Rombouts, Jeroen, et al.
Published: (2024)
Adaptive Multi-task Learning for Probabilistic Load Forecasting
by: Zaballa, Onintze, et al.
Published: (2025)
by: Zaballa, Onintze, et al.
Published: (2025)
AutoML Algorithms for Online Generalized Additive Model Selection: Application to Electricity Demand Forecasting
by: Das, Keshav, et al.
Published: (2025)
by: Das, Keshav, et al.
Published: (2025)
Enhanced Renewable Energy Forecasting using Context-Aware Conformal Prediction
by: Moradi, Alireza, et al.
Published: (2025)
by: Moradi, Alireza, et al.
Published: (2025)
Dynamic Attention (DynAttn): Interpretable High-Dimensional Spatio-Temporal Forecasting (with Application to Conflict Fatalities)
by: Iacus, Stefano M., et al.
Published: (2025)
by: Iacus, Stefano M., et al.
Published: (2025)
Application of Machine Learning in Stock Market Forecasting: A Case Study of Disney Stock
by: Huang, Dengxin
Published: (2023)
by: Huang, Dengxin
Published: (2023)
Spatio-temporal DeepKriging in PyTorch: A Supplementary Application to Precipitation Data for Interpolation and Probabilistic Forecasting
by: Nag, Pratik
Published: (2025)
by: Nag, Pratik
Published: (2025)
Ensemble Survival Analysis for Preclinical Cognitive Decline Prediction in Alzheimer's Disease Using Longitudinal Biomarkers
by: Ghosh, Dhrubajyoti, et al.
Published: (2025)
by: Ghosh, Dhrubajyoti, et al.
Published: (2025)
Cross-Domain Offshore Wind Power Forecasting: Transfer Learning Through Meteorological Clusters
by: Weisser, Dominic, et al.
Published: (2026)
by: Weisser, Dominic, et al.
Published: (2026)
Dynamic Classification of Latent Disease Progression with Auxiliary Surrogate Labels
by: Cai, Zexi, et al.
Published: (2024)
by: Cai, Zexi, et al.
Published: (2024)
Temporal Subtyping of Alzheimer's Disease Using Medical Conditions Preceding Alzheimer's Disease Onset in Electronic Health Records
by: He, Zhe, et al.
Published: (2022)
by: He, Zhe, et al.
Published: (2022)
Forecasting Monthly Residential Natural Gas Demand Using Just-In-Time-Learning Modeling
by: Alakent, Burak, et al.
Published: (2025)
by: Alakent, Burak, et al.
Published: (2025)
Machine Learning Classification of Alzheimer's Disease Stages Using Cerebrospinal Fluid Biomarkers Alone
by: Tiwari, Vivek Kumar, et al.
Published: (2024)
by: Tiwari, Vivek Kumar, et al.
Published: (2024)
Sparse Variational Contaminated Noise Gaussian Process Regression with Applications in Geomagnetic Perturbations Forecasting
by: Iong, Daniel, et al.
Published: (2024)
by: Iong, Daniel, et al.
Published: (2024)
Informed Forecasting: Leveraging Auxiliary Knowledge to Boost LLM Performance on Time Series Forecasting
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2025)
by: Ghasemloo, Mohammadmahdi, et al.
Published: (2025)
Weather-Related Crash Risk Forecasting: A Deep Learning Approach for Heterogenous Spatiotemporal Data
by: Ogungbire, Abimbola, et al.
Published: (2026)
by: Ogungbire, Abimbola, et al.
Published: (2026)
Moving Towards Automated Interstellar Boundary Explorer Data Selection with LOTUS
by: Stricklin, Madeline A., et al.
Published: (2024)
by: Stricklin, Madeline A., et al.
Published: (2024)
Modeling Parkinson's Disease Progression Using Longitudinal Voice Biomarkers: A Comparative Study of Statistical and Neural Mixed-Effects Models
by: Tong, Ran, et al.
Published: (2025)
by: Tong, Ran, et al.
Published: (2025)
Generative Probabilistic Time Series Forecasting and Applications in Grid Operations
by: Wang, Xinyi, et al.
Published: (2024)
by: Wang, Xinyi, et al.
Published: (2024)
Long-Term Spatio-Temporal Forecasting of Monthly Rainfall in West Bengal Using Ensemble Learning Approaches
by: Adhikary, Jishu, et al.
Published: (2025)
by: Adhikary, Jishu, et al.
Published: (2025)
BuildSTG: A Multi-building Energy Load Forecasting Method using Spatio-Temporal Graph Neural Network
by: Liu, Yongzheng, et al.
Published: (2025)
by: Liu, Yongzheng, et al.
Published: (2025)
Improving Geopolitical Forecasts with Bayesian Networks
by: Martin, Matthew
Published: (2026)
by: Martin, Matthew
Published: (2026)
Simplifying Random Forests' Probabilistic Forecasts
by: Koster, Nils, et al.
Published: (2024)
by: Koster, Nils, et al.
Published: (2024)
Differentially Private Modeling of Disease Transmission within Human Contact Networks
by: Hod, Shlomi, et al.
Published: (2026)
by: Hod, Shlomi, et al.
Published: (2026)
Similar Items
-
Mapping Incidence and Prevalence Peak Data for SIR Forecasting Applications
by: Murph, Alexander C., et al.
Published: (2024) -
Leveraging Synthetic and Genetic Data to Improve Epidemic Forecasting
by: Osthus, Dave, et al.
Published: (2026) -
Code for the publication "Beyond Equal Weights: A Disease-agnostic Approach to Ensemble Learning for Infectious Disease Forecasting"
by: Murph, Alexander C., et al.
Published: (2025) -
EpiFFORMA: Disease-Agnostic Ensemble Weighting for Forecasting Emerging Epidemic Time Series without Historical Data
by: Murph, Alexander C., et al.
Published: (2025) -
Bayesian Statistical Inversion for High-Dimensional Computer Model Output and Spatially Distributed Counts
by: Barnett, Steven D., et al.
Published: (2025)