| Introducing digital twins to agriculture C Pylianidis, S Osinga, IN Athanasiadis Computers and Electronics in Agriculture 184, 105942, 2021 | 315 | 2021 |
| Machine learning for large-scale crop yield forecasting D Paudel, H Boogaard, A de Wit, S Janssen, S Osinga, C Pylianidis, ... Agricultural Systems 187, 103016, 2021 | 183 | 2021 |
| Simulation-assisted machine learning for operational digital twins C Pylianidis, V Snow, H Overweg, S Osinga, J Kean, IN Athanasiadis Environmental Modelling & Software 148, 105274, 2022 | 25 | 2022 |
| IN Athanasiadis Introducing digital twins to agriculture., 2021, 184 C Pylianidis, S Osinga DOI: https://doi. org/10.1016/j. compag, 105942, 2020 | 9 | 2020 |
| Deeporyza: a knowledge guided machine learning model for rice growth simulation J Han, L Shi, C Pylianidis, Q Yang, IN Athanasiadis 2nd AAAI Workshop on AI for Agriculture and Food Systems, 2023 | 4 | 2023 |
| Location-specific vs location-agnostic machine learning metamodels for predicting pasture nitrogen response rate C Pylianidis, V Snow, D Holzworth, J Bryant, IN Athanasiadis Pattern Recognition. ICPR International Workshops and Challenges: Virtual …, 2021 | 4 | 2021 |
| Introducing digital twins to agriculture C Pylianidis, S Osinga, IN Athanasiadis Netherlands: Elsevier BV, 2020 | 3 | 2020 |
| Integrating processed-based models and machine learning for crop yield prediction MGJ Kallenberg, B Maestrini, R van Bree, P Ravensbergen, C Pylianidis, ... arXiv preprint arXiv:2307.13466, 2023 | 2 | 2023 |
| Learning latent representations for operational nitrogen response rate prediction C Pylianidis, IN Athanasiadis arXiv preprint arXiv:2205.09025, 2022 | 1 | 2022 |
| Sample data for" Machine learning for large-scale forecasting" D Paudel, H Boogaard, A de Wit, S Janssen, S Osinga, C Pylianidis, ... | 1 | 2021 |
| Domain adaptation with transfer learning for pasture digital twins C Pylianidis, MGJ Kallenberg, IN Athanasiadis Environmental Data Science 3, e8, 2024 | | 2024 |
| Operationalizing digital twins in agriculture with machine learning C Pylianidis PQDT-Global, 2023 | | 2023 |
| Comparing machine learning metamodels of different scale for pasture nitrogen response rate prediction C Pylianidis, V Snow, H Overweg, IN Athanasiadis EGU General Assembly Conference Abstracts, EGU21-8279, 2021 | | 2021 |
| Introducing digital twins for cropping systems C Pylianidis, IN Athanasiadis, SA Osinga Wageningen Data Science Week, 2020 | | 2020 |
| Machine learning surrogates for crop models C Pylianidis | | 2020 |
| Metamodels for Crop Growth Models B Maestrini, C Pylianidis, J Kool, K Jindo, D Paudel, I Athanasiadis, ... ASA, CSSA and SSSA International Annual Meetings (2020)| VIRTUAL, 2020 | | 2020 |
