Marco Virgolin
Marco Virgolin
Postdoc, Chalmers University of Technology
Email verificata su cwi.nl - Home page
Titolo
Citata da
Citata da
Anno
Scalable genetic programming by gene-pool optimal mixing and input-space entropy-based building-block learning
M Virgolin, T Alderliesten, C Witteveen, PAN Bosman
Proceedings of the Genetic and Evolutionary Computation Conference, 1041-1048, 2017
152017
Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivors
M Virgolin, T Alderliesten, A Bel, C Witteveen, PAN Bosman
Proceedings of the Genetic and Evolutionary Computation Conference, 1395-1402, 2018
112018
On the feasibility of automatically selecting similar patients in highly individualized radiotherapy dose reconstruction for historic data of pediatric cancer survivors
M Virgolin, IWEM Van Dijk, J Wiersma, CM Ronckers, C Witteveen, A Bel, ...
Medical physics 45 (4), 1504-1517, 2018
72018
Unveiling evolutionary algorithm representation with DU maps
E Medvet, M Virgolin, M Castelli, PAN Bosman, I Gonšalves, T Tušar
Genetic Programming and Evolvable Machines 19 (3), 351-389, 2018
62018
Improving Model-based Genetic Programming for Symbolic Regression of Small Expressions
M Virgolin, T Alderliesten, C Witteveen, PAN Bosman
arXiv preprint arXiv:1904.02050, 2019
4*2019
Evolutionary learning of syntax patterns for genic interaction extraction
A Bartoli, A De Lorenzo, E Medvet, F Tarlao, M Virgolin
Proceedings of the 2015 Annual Conference on Genetic and Evolutionaryá…, 2015
32015
Automatic generation of three-dimensional dose reconstruction data for two-dimensional radiotherapy plans for historically treated patients
Z Wang, M Virgolin, PAN Bosman, KF Crama, BV Balgobind, A Bel, ...
Journal of Medical Imaging 7 (1), 015001, 2020
22020
Linear scaling with and within semantic backpropagation-based genetic programming for symbolic regression
M Virgolin, T Alderliesten, PAN Bosman
Proceedings of the Genetic and Evolutionary Computation Conference, 1084-1092, 2019
22019
On Explaining Machine Learning Models by Evolving Crucial and Compact Features
M Virgolin, T Alderliesten, PAN Bosman
arXiv preprint arXiv:1907.02260, 2019
22019
How do patient characteristics and anatomical features correlate to accuracy of organ dose reconstruction for Wilms’ tumor radiation treatment plans when using a surrogateá…
Z Wang, BV Balgobind, M Virgolin, IWEM van Dijk, J Wiersma, ...
Journal of Radiological Protection 39 (2), 598, 2019
22019
Automatic radiotherapy plan emulation for 3D dose reconstruction to enable big data analysis for historically treated patients
Z Wang, M Virgolin, PAN Bosman, BV Balgobind, A Bel, T Alderliesten
Medical Imaging 2019: Imaging Informatics for Healthcare, Research, andá…, 2019
12019
Learning a Formula of Interpretability to Learn Interpretable Formulas
M Virgolin, A De Lorenzo, E Medvet, F Randone
arXiv preprint arXiv:2004.11170, 2020
2020
Local Search is a Remarkably Strong Baseline for Neural Architecture Search
TD Ottelander, A Dushatskiy, M Virgolin, PAN Bosman
arXiv preprint arXiv:2004.08996, 2020
2020
Machine learning for automatic construction of pediatric abdominal phantoms for radiation dose reconstruction
M Virgolin, Z Wang, T Alderliesten, PAN Bosman
Medical Imaging 2020: Imaging Informatics for Healthcare, Research, andá…, 2020
2020
Surrogate-free machine learning-based organ dose reconstruction for pediatric abdominal radiotherapy
M Virgolin, Z Wang, BV Balgobind, I van Dijk, J Wiersma, PS Kroon, ...
arXiv preprint arXiv:2002.07161, 2020
2020
Machine learning for automatic construction of pseudo-realistic pediatric abdominal phantoms
M Virgolin, Z Wang, T Alderliesten, PAN Bosman
arXiv preprint arXiv:1909.03723, 2019
2019
Relating anatomical variations and patient features with dose-reconstruction accuracy of a 3D dose-reconstruction approach using CT scans of recently-treated children
Z Wang, M Virgolin, I IWEM Dijk, J Wiersma, C Ronckers, F Oldenburger, ...
2017
Learning to Associate Distances with Historical Patient Data to Enable Fine-grained Studying of Late Adverse Effects of Paediatric Radiotherapy: Data, Methodology, and Firstá…
M Virgolin, I van Dijk, J Wiersma, CM Ronckers, C Witteveen, C Rasch, ...
Proceedings of the International Conference on the use of Computers iná…, 2016
2016
Model-based Genetic Programming with GOMEA for Symbolic Regression of Small Expressions
M Virgolin, T Alderliesten, C Witteveen, PAN Bosman
Design and Application of Gene-pool Optimal Mixing Evolutionary Algorithms for Genetic Programming
M Virgolin
Delft University of Technology, 0
Il sistema al momento non pu˛ eseguire l'operazione. Riprova pi¨ tardi.
Articoli 1–20