|A collaborative multiyear, multimodel assessment of seasonal influenza forecasting in the United States|
NG Reich, LC Brooks, SJ Fox, S Kandula, CJ McGowan, E Moore, ...
Proceedings of the National Academy of Sciences 116 (8), 3146-3154, 2019
|Epidemic forecasting is messier than weather forecasting: The role of human behavior and internet data streams in epidemic forecast|
KR Moran, G Fairchild, N Generous, K Hickmann, D Osthus, ...
The Journal of infectious diseases 214 (suppl_4), S404-S408, 2016
|Validity of 24-h physical activity recall: physical activity measurement survey|
GJ Welk, Y Kim, B Stanfill, DA Osthus, AM Calabro, SM Nusser, ...
Medicine and science in sports and exercise 46 (10), 2014
|Forecasting seasonal influenza with a state-space SIR model|
D Osthus, KS Hickmann, PC Caragea, D Higdon, SY Del Valle
The annals of applied statistics 11 (1), 202, 2017
|Dynamic Bayesian influenza forecasting in the United States with hierarchical discrepancy (with discussion)|
D Osthus, J Gattiker, R Priedhorsky, SY Del Valle
Bayesian Analysis 14 (1), 261-312, 2019
|Measuring global disease with Wikipedia: Success, failure, and a research agenda|
R Priedhorsky, D Osthus, AR Daughton, KR Moran, N Generous, ...
Proceedings of the 2017 ACM Conference on Computer Supported Cooperative …, 2017
|Even a good influenza forecasting model can benefit from internet-based nowcasts, but those benefits are limited|
D Osthus, AR Daughton, R Priedhorsky
PLoS computational biology 15 (2), e1006599, 2019
|Quantifying topological uncertainty in fractured systems using graph theory and machine learning|
G Srinivasan, JD Hyman, DA Osthus, BA Moore, D O’Malley, S Karra, ...
Scientific reports 8 (1), 1-11, 2018
|Identifying backbones in three-dimensional discrete fracture networks: A bipartite graph-based approach|
JD Hyman, A Hagberg, D Osthus, S Srinivasan, H Viswanathan, ...
Multiscale Modeling & Simulation 16 (4), 1948-1968, 2018
|Dynamic linear models for forecasting of radiation belt electrons and limitations on physical interpretation of predictive models|
D Osthus, PC Caragea, D Higdon, SK Morley, GD Reeves, BP Weaver
Space Weather 12 (6), 426-446, 2014
|Calibrating the stress-time curve of a combined finite-discrete element method to a Split Hopkinson Pressure Bar experiment|
D Osthus, HC Godinez, E Rougier, G Srinivasan
International Journal of Rock Mechanics and Mining Sciences 106, 278-288, 2018
|Reply to Bracher: Scoring probabilistic forecasts to maximize public health interpretability|
NG Reich, D Osthus, EL Ray, TK Yamana, M Biggerstaff, MA Johansson, ...
Proceedings of the National Academy of Sciences of the United States of …, 2019
|Accuracy of real-time multi-model ensemble forecasts for seasonal influenza in the US|
NG Reich, CJ McGowan, TK Yamana, A Tushar, EL Ray, D Osthus, ...
PLoS computational biology 15 (11), e1007486, 2019
|Prediction uncertainties beyond the range of experience: a case study in inertial confinement fusion implosion experiments|
D Osthus, SA Vander Wiel, NM Hoffman, FJ Wysocki
SIAM/ASA Journal on Uncertainty Quantification 7 (2), 604-633, 2019
|Fourier amplitude sensitivity test applied to dynamic combined finite‐discrete element methods–based simulations|
HC Godinez, E Rougier, D Osthus, Z Lei, E Knight, G Srinivasan
International Journal for Numerical and Analytical Methods in Geomechanics …, 2019
|Forecasting seasonal influenza in the US: A collaborative multi-year, multi-model assessment of forecast performance|
NG Reich, L Brooks, S Fox, S Kandula, C McGowan, E Moore, D Osthus, ...
bioRxiv, 397190, 2018
|Imputation for multisource data with comparison and assessment techniques|
E Casleton, D Osthus, K Van Buren
Applied Stochastic Models in Business and Industry 34 (1), 44-60, 2018
|Google Health Trends performance reflecting dengue incidence for the Brazilian states|
D Romero-Alvarez, N Parikh, D Osthus, K Martinez, N Generous, ...
BMC infectious diseases 20, 1-15, 2020
|Deceptiveness of internet data for disease surveillance|
R Priedhorsky, D Osthus, AR Daughton, KR Moran, A Culotta
arXiv preprint arXiv:1711.06241, 2017
|A Probabilistic Clustering Approach for Identifying Primary Subnetworks of Discrete Fracture Networks with Quantified Uncertainty|
D Osthus, JD Hyman, S Karra, N Panda, G Srinivasan
SIAM/ASA Journal on Uncertainty Quantification 8 (2), 573-600, 2020