| Electricity price forecasting for nord pool data R Beigaite, T Krilavičius, KL Man 2018 International conference on platform technology and service (PlatCon), 1-6, 2018 | 50 | 2018 |
| Identifying climate thresholds for dominant natural vegetation types at the global scale using machine learning: Average climate versus extremes R Beigaitė, H Tang, A Bryn, O Skarpaas, F Stordal, JW Bjerke, I Žliobaitė Global Change Biology 28 (11), 3557-3579, 2022 | 34 | 2022 |
| Spatial cross-validation for globally distributed data R Beigaitė, M Mechenich, I Žliobaitė International Conference on Discovery Science, 127-140, 2022 | 10 | 2022 |
| Multi-output regression with structurally incomplete target labels: A case study of modelling global vegetation cover R Beigaitė, J Read, I Žliobaitė Ecological Informatics 72, 101849, 2022 | 4 | 2022 |
| Multi-output prediction of global vegetation distribution with incomplete data R Beigaite, J Read, I Zliobaite ICML Workshop on the Art of Learning with Missing Values (Artemiss), 2020 | 1 | 2020 |
| Backward Inference in Probabilistic Regressor Chains with Distributional Constraints E Antonenko, M Mechenich, R Beigaitė, I Žliobaitė, J Read International Symposium on Intelligent Data Analysis, 43-55, 2024 | | 2024 |
| Machine Learning Methods for Globally Structured Multi-Target Data R Beigaite | | 2023 |
| Elektros energijos kainų prognozavimas R Beigaitė | | 2018 |
