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Anton Bouter
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2020 – today
- 2024
- [i5]Georgios Andreadis, Joas I. Mulder, Anton Bouter, Peter A. N. Bosman, Tanja Alderliesten:
A Tournament of Transformation Models: B-Spline-based vs. Mesh-based Multi-Objective Deformable Image Registration. CoRR abs/2401.16867 (2024) - 2023
- [c11]Anton Bouter, Peter A. N. Bosman:
A Joint Python/C++ Library for Efficient yet Accessible Black-Box and Gray-Box Optimization with GOMEA. GECCO Companion 2023: 1864-1872 - [i4]Anton Bouter, Peter A. N. Bosman:
A Joint Python/C++ Library for Efficient yet Accessible Black-Box and Gray-Box Optimization with GOMEA. CoRR abs/2305.06246 (2023) - 2022
- [c10]Anton Bouter, Peter A. N. Bosman:
GPU-accelerated parallel gene-pool optimal mixing in a gray-box optimization setting. GECCO 2022: 675-683 - [c9]Renzo J. Scholman, Anton Bouter, Leah R. M. Dickhoff, Tanja Alderliesten, Peter A. N. Bosman:
Obtaining Smoothly Navigable Approximation Sets in Bi-objective Multi-modal Optimization. PPSN (2) 2022: 247-262 - [i3]Anton Bouter, Peter A. N. Bosman:
GPU-Accelerated Parallel Gene-pool Optimal Mixing in a Gray-Box Optimization Setting. CoRR abs/2203.08680 (2022) - [i2]Renzo J. Scholman, Anton Bouter, Leah R. M. Dickhoff, Tanja Alderliesten, Peter A. N. Bosman:
Obtaining Smoothly Navigable Approximation Sets in Bi-Objective Multi-Modal Optimization. CoRR abs/2203.09214 (2022) - 2021
- [j2]Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman:
Achieving Highly Scalable Evolutionary Real-Valued Optimization by Exploiting Partial Evaluations. Evol. Comput. 29(1): 129-155 (2021) - [j1]Chantal Olieman, Anton Bouter, Peter A. N. Bosman:
Fitness-Based Linkage Learning in the Real-Valued Gene-Pool Optimal Mixing Evolutionary Algorithm. IEEE Trans. Evol. Comput. 25(2): 358-370 (2021) - [c8]Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman:
GPU-Accelerated Parallel Gene-pool Optimal Mixing Applied to Multi-Objective Deformable Image Registration. CEC 2021: 2539-2548 - [i1]Arkadiy Dushatskiy, Marco Virgolin, Anton Bouter, Dirk Thierens, Peter A. N. Bosman:
Parameterless Gene-pool Optimal Mixing Evolutionary Algorithms. CoRR abs/2109.05259 (2021) - 2020
- [c7]Anton Bouter, Stefanus C. Maree, Tanja Alderliesten, Peter A. N. Bosman:
Leveraging conditional linkage models in gray-box optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2020: 603-611
2010 – 2019
- 2018
- [c6]Anton Bouter, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman:
Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problems. GECCO 2018: 1199-1206 - 2017
- [c5]Anton Bouter, Ngoc Hoang Luong, Cees Witteveen, Tanja Alderliesten, Peter A. N. Bosman:
The multi-objective real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2017: 537-544 - [c4]Anton Bouter, Tanja Alderliesten, Cees Witteveen, Peter A. N. Bosman:
Exploiting linkage information in real-valued optimization with the real-valued gene-pool optimal mixing evolutionary algorithm. GECCO 2017: 705-712 - [c3]Ngoc Hoang Luong, Anton Bouter, Marjolein C. van der Meer, Yury Niatsetski, Cees Witteveen, Arjan Bel, Tanja Alderliesten, Peter A. N. Bosman:
Efficient, effective, and insightful tackling of the high-dose-rate brachytherapy treatment planning problem for prostate cancer using evolutionary multi-objective optimization algorithms. GECCO (Companion) 2017: 1372-1379 - [c2]Anton Bouter, Kleopatra Pirpinia, Tanja Alderliesten, Peter A. N. Bosman:
Spatial redistribution of irregularly-spaced pareto fronts for more intuitive navigation and solution selection. GECCO (Companion) 2017: 1697-1704 - [c1]Anton Bouter, Tanja Alderliesten, Peter A. N. Bosman:
A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality. Medical Imaging: Image Processing 2017: 1013312
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last updated on 2024-04-25 05:52 CEST by the dblp team
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