| Elastic depths for detecting shape anomalies in functional data T Harris, JD Tucker, B Li, L Shand Technometrics 63 (4), 466-476, 2021 | 31 | 2021 |
| Scalable multiple changepoint detection for functional data sequences T Harris, B Li, JD Tucker Environmetrics 33 (2), e2710, 2022 | 13 | 2022 |
| The effect of co-location on human communication networks D Carmody, M Mazzarello, P Santi, T Harris, S Lehmann, T Abbiasov, ... Nature Computational Science 2 (8), 494-503, 2022 | 10 | 2022 |
| Forecasting West Nile virus with graph neural networks: Harnessing spatial dependence in irregularly sampled geospatial data A Tonks, T Harris, B Li, W Brown, R Smith arXiv preprint arXiv:2212.11367, 2022 | 6 | 2022 |
| Evaluating proxy influence in assimilated paleoclimate reconstructions—Testing the exchangeability of two ensembles of spatial processes T Harris, B Li, NJ Steiger, JE Smerdon, N Narisetty, JD Tucker Journal of the American Statistical Association 116 (535), 1100-1113, 2021 | 4 | 2021 |
| Asynchronous changepoint estimation for spatially correlated functional time series M Wang, T Harris, B Li Journal of Agricultural, Biological and Environmental Statistics 28 (1), 157-176, 2023 | 2 | 2023 |
| Multimodel ensemble analysis with neural network Gaussian processes T Harris, B Li, R Sriver The Annals of Applied Statistics 17 (4), 3403-3425, 2023 | 1 | 2023 |
| Phenology and environmental predictors of Triatoma sanguisuga dispersal in east-central Texas, United States JP Fimbres-Macias, TA Harris, SA Hamer, GL Hamer Acta Tropica 240, 106862, 2023 | 1 | 2023 |
| Validating Climate Models with Spherical Convolutional Wasserstein Distance RC Garrett, T Harris, B Li, Z Wang arXiv preprint arXiv:2401.14657, 2024 | | 2024 |
| An Application of Graph Neural Networks to Spatial Graphs: Harnessing Spatial Dependence in the Spread of West Nile Virus A Tonks, T Harris, B Li, WM Brown, RL Smith AGU23, 2023 | | 2023 |
| Evaluating Climate Models with Sliced Elastic Distance RC Garrett, T Harris, B Li arXiv preprint arXiv:2307.08685, 2023 | | 2023 |
| Asynchronous Changepoint Estimation for Spatially Correlated Functional Time Series (vol 28, pg 157, 2022) M Wang, T Harris, B Li JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 28 (1), 177-177, 2023 | | 2023 |
| Correction to: Asynchronous Changepoint Estimation for Spatially Correlated Functional Time Series M Wang, T Harris, B Li Journal of Agricultural, Biological and Environmental Statistics 28 (1), 177-177, 2023 | | 2023 |
| Machine learning applications for estimation of greenhouse gas emissions using multiple satellite images. RJ Ringer, H Yoon, T Kadeethum, T Harris Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Using Graph Neural Networks to Forecast West Nile Virus with Trap and Weather Data A Tonks, T Harris, B Li, WM Brown, RL Smith AGU Fall Meeting Abstracts 2022, GH25C-0616, 2022 | | 2022 |
| Deep learning-based spatio-temporal estimate of greenhouse gas emissions using satellite data H Yoon, T Kadeethum, RJ Ringer, T Harris Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2022 | | 2022 |
| Bayesian Changepoint Estimation for Spatially Indexed Functional Time Series M Wang, T Harris, B Li arXiv preprint arXiv:2201.02742, 2022 | | 2022 |
| Functional data methods for climatological processes TA Harris University of Illinois at Urbana-Champaign, 2021 | | 2021 |
| Variational Target Encoding for Integrating Climate Models T Harris, B Li AGU Fall Meeting Abstracts 2020, A073-04, 2020 | | 2020 |
| Functional Change Point Detection with Nonnegative Matrix Factorization. T Harris, JD Tucker Sandia National Lab.(SNL-NM), Albuquerque, NM (United States), 2019 | | 2019 |
