| Shape-constrained symbolic regression—improving extrapolation with prior knowledge G Kronberger, FO de França, B Burlacu, C Haider, M Kommenda Evolutionary computation 30 (1), 75-98, 2022 | 39 | 2022 |
| Shape-constrained multi-objective genetic programming for symbolic regression C Haider, FO de França, B Burlacu, G Kronberger Applied Soft Computing 132, 109855, 2023 | 12 | 2023 |
| Using shape constraints for improving symbolic regression models C Haider, FO de França, B Burlacu, G Kronberger arXiv preprint arXiv:2107.09458, 2021 | 9 | 2021 |
| Comparing optimistic and pessimistic constraint evaluation in shape-constrained symbolic regression C Haider, FO de França, G Kronberger, B Burlacu Proceedings of the Genetic and Evolutionary Computation Conference, 938-945, 2022 | 6 | 2022 |
| TreeDom: a graphical web tool for analysing domain architecture evolution C Haider, M Kavic, ELL Sonnhammer Bioinformatics 32 (15), 2384-2385, 2016 | 4 | 2016 |
| Shape-constrained Symbolic Regression: Real-World Applications in Magnetization, Extrusion and Data Validation C Haider, FO de Franca, B Burlacu, F Bachinger, G Kronberger, ... Genetic Programming Theory and Practice XX, 225-240, 2024 | 1 | 2024 |
| Improving the flexibility of shape-constrained symbolic regression with extended constraints D Piringer, S Wagner, C Haider, A Fohler, S Silber, M Affenzeller International Conference on Computer Aided Systems Theory, 155-163, 2022 | 1 | 2022 |
| Shape-constrained symbolic regression with NSGA-III C Haider, G Kronberger International Conference on Computer Aided Systems Theory, 164-172, 2022 | 1 | 2022 |
| Identification and classification of objects and motions in microscopy images of biological samples using heuristic algorithms SM Winkler, S Schaller, D Borgmann, L Obritzberger, V Dorfer, C Haider, ... Computational Intelligence and Efficiency in Engineering Systems, 103-117, 2015 | | 2015 |
