Name
Affiliation
Papers
PETER A. N. BOSMAN
Center for Mathematics and Computer Science, Amsterdam, Netherlands
75
Collaborators
Citations 
PageRank 
62
507
49.04
Referers 
Referees 
References 
763
787
640
Search Limit
100787
Title
Citations
PageRank
Year
Gene-pool Optimal Mixing in Cartesian Genetic Programming00.342022
Hybridizing Hypervolume-Based Evolutionary Algorithms and Gradient Descent by Dynamic Resource Allocation00.342022
Obtaining Smoothly Navigable Approximation Sets in Bi-objective Multi-modal Optimization00.342022
Observer Variation-Aware Medical Image Segmentation By Combining Deep Learning And Surrogate-Assisted Genetic Algorithms00.342020
On explaining machine learning models by evolving crucial and compact features.10.352020
An End-To-End Deep Learning Approach For Landmark Detection And Matching In Medical Images00.342020
Fast and insightful bi-objective optimization for prostate cancer treatment planning with high-dose-rate brachytherapy.00.342019
Evolutionary Machine Learning for Multi-Objective Class Solutions in Medical Deformable Image Registration00.342019
Evolutionary multi-objective meta-optimization of deformation and tissue removal parameters improves the performance of deformable image registration of pre- and post-surgery images.00.342019
A Model-based Genetic Programming Approach for Symbolic Regression of Small Expressions.00.342019
Real-valued evolutionary multi-modal multi-objective optimization by hill-valley clustering10.352019
Multi-objective Gene-pool Optimal Mixing Evolutionary Algorithm with the Interleaved Multi-start Scheme.20.362018
Real-valued evolutionary multi-modal optimization driven by hill-valley clustering.40.402018
GAMBIT: A Parameterless Model-Based Evolutionary Algorithm for Mixed-Integer Problems.00.342018
Learning bayesian network structures with GOMEA.00.342018
Application and benchmarking of multi-objective evolutionary algorithms on high-dose-rate brachytherapy planning for prostate cancer treatment.40.492018
Benchmarking the Hill-Valley Evolutionary Algorithm for the GECCO 2018 Competition on Niching Methods Multimodal Optimization.00.342018
Unveiling evolutionary algorithm representation with DU maps.10.362018
The importance of implementation details and parameter settings in black-box optimization: a case study on Gaussian estimation-of-distribution algorithms and circles-in-a-square packing problems.10.362018
Improving the performance of MO-RV-GOMEA on problems with many objectives using tchebycheff scalarizations.00.342018
Model-based evolutionary algorithms: GECCO 2017 tutorial.00.342018
Niching an estimation-of-distribution algorithm by hierarchical Gaussian mixture learning.30.422017
A novel model-based evolutionary algorithm for multi-objective deformable image registration with content mismatch and large deformations: benchmarking efficiency and quality.20.412017
Expanding from Discrete Cartesian to Permutation Gene-pool Optimal Mixing Evolutionary Algorithms.40.432016
Smart grid initialization reduces the computational complexity of multi-objective image registration based on a dual-dynamic transformation model to account for large anatomical differences.00.342016
A first step toward uncovering the truth about weight tuning in deformable image registration.10.362016
GECCO'16 Model-Based Evolutionary Algorithms (MBEA) Workshop Chairs' Welcome.00.342016
On the usefulness of gradient information in multi-objective deformable image registration using a B-spline-based dual-dynamic transformation model: comparison of three optimization algorithms00.342015
Getting the most out of additional guidance information in deformable image registration by leveraging multi-objective optimization10.362015
In Search of Optimal Linkage Trees00.342015
Diversifying Multi-Objective Gradient Techniques and their Role in Hybrid Multi-Objective Evolutionary Algorithms for Deformable Medical Image Registration00.342015
Exploiting Linkage Information and Problem-Specific Knowledge in Evolutionary Distribution Network Expansion Planning30.432015
A Clustering-Based Model-Building EA for Optimization Problems with Binary and Real-Valued Variables10.352015
A multi-resolution strategy for a multi-objective deformable image registration framework that accommodates large anatomical differences00.342014
Combining Model-Based Eas For Mixed-Integer Problems10.382014
A novel population-based multi-objective CMA-ES and the impact of different constraint handling techniques.10.362014
Multi-objective gene-pool optimal mixing evolutionary algorithms.50.462014
Market Garden: A Simulation Environment for Research and User Experience in Smart Grids.00.342014
Efficiency enhancements for evolutionary capacity planning in distribution grids.00.342014
Practice-oriented optimization of distribution network planning using metaheuristic algorithms40.602014
Medium-Voltage Distribution Network Expansion Planning With Gene-Pool Optimal Mixing Evolutionary Algorithms40.682013
Deformable image registration by multi-objective optimization using a dual-dynamic transformation model to account for large anatomical differences30.442013
Market Garden: A Scalable Research Environment for Heterogeneous Electricity Markets.10.432013
Benchmarking parameter-free amalgam on functions with and without noise20.382013
Learning the neighborhood with the linkage tree genetic algorithm00.342012
Evolvability analysis of the linkage tree genetic algorithm30.402012
Predetermined versus learned linkage models30.522012
On Gradients and Hybrid Evolutionary Algorithms for Real-Valued Multiobjective Optimization270.972012
On measures to build linkage trees in LTGA30.382012
Multi-objective optimization for deformable image registration: proof of concept40.482012
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