| Metal oxide based multisensor array and portable database for field analysis of antioxidants E Sharpe, R Bradley, T Frasco, D Jayathilaka, A Marsh, S Andreescu Sensors and Actuators B: Chemical 193, 552-562, 2014 | 59 | 2014 |
| Real-time forecasting of time series in financial markets using sequentially trained dual-LSTM K Gajamannage, Y Park, DI Jayathilake Expert Systems with Applications, 119879, 2023 | 24 | 2023 |
| Understanding the role of hydrologic model structures on evapotranspiration-driven sensitivity DI Jayathilake, T Smith Hydrological Sciences Journal 65 (9), 1474-1489, 2020 | 14 | 2020 |
| Assessing the impact of PET estimation methods on hydrologic model performance DI Jayathilake, T Smith Hydrology Research 52 (2), 373-388, 2021 | 13 | 2021 |
| Recurrent neural networks for dynamical systems: Applications to ordinary differential equations, collective motion, and hydrological modeling K Gajamannage, DI Jayathilake, Y Park, EM Bollt Chaos: An Interdisciplinary Journal of Nonlinear Science 33 (1), 013109, 2023 | 9 | 2023 |
| Recurrent Neural Networks for Dynamical Systems: Applications to Ordinary Differential Equations, Collective Motion, and Hydrological Modeling Y Park, K Gajamannage, DI Jayathilake, EM Bollt arXiv preprint arXiv:2202.07022, 2022 | 9 | 2022 |
| Predicting the temporal transferability of model parameters through a hydrological signature analysis DI Jayathilake, T Smith Frontiers of Earth Science 14 (1), 110-123, 2020 | 6 | 2020 |
| Identifying the Influence of Systematic Errors in Potential Evapotranspiration on Rainfall–Runoff Models DI Jayathilake, T Smith Journal of Hydrologic Engineering 27 (2), 04021047, 2022 | 2 | 2022 |
| Exploring the Sensitivity of Hydrologic Models to Potential Evapotranspiration Inputs DI Jayathilake Clarkson University, 2019 | | 2019 |
| Multi-Model Analysis to Understand the Sensitivity of Rainfall-Runoff Model Structure to Potential Evapotranspiration Inputs. DI Jayathilake, TJ Smith AGU Fall Meeting Abstracts 2018, H43D-2425, 2018 | | 2018 |
| Sensitivity of Rainfall-runoff Model Parametrization and Performance to Potential Evaporation Inputs DI Jayathilake, TJ Smith AGU Fall Meeting Abstracts 2017, H23C-1675, 2017 | | 2017 |
| Can Signatures Predict Hydrologic Model Performance in Validation Mode? DI Jayathilake, TJ Smith 2015 AGU Fall Meeting, 2015 | | 2015 |
| An Alternative View of the Calibration-validation Problem: Seeking to Identify Predictive Hydrologic Signatures: A Thesis D Jayathilake Clarkson University, 2014 | | 2014 |
