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Anil Yaman
Anil Yaman
Assistant Professor, Vrije Universiteit Amsterdam
Verified email at vu.nl - Homepage
Title
Cited by
Cited by
Year
Evolutionary approach to constructing a deep feedforward neural network for prediction of electronic coupling elements in molecular materials
O Caylak, A Yaman, B Baumeier
Journal of chemical theory and computation 15 (3), 1777-1784, 2019
212019
A comparison of three Differential Evolution strategies in terms of early convergence with different population sizes
A Yaman, G Iacca, F Caraffini
AIP Conference Proceedings 2070 (1), 020002, 2019
162019
Topological Insights into Sparse Neural Networks
S Liu, TT van der Lee, A Yaman, Z Atashgahi, D Ferrar, G Sokar, ...
Proceedings of the European Conference on Machine Learning and Principles …, 2020
13*2020
Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolution
A Yaman, DC Mocanu, G Iacca, G Fletcher, M Pechenizkiy
GECCO'18: Genetic and Evolutionary Computation Conference, July 15--19, 2018 …, 2018
132018
The representativeness of eligible patients in type 2 diabetes trials: a case study using GIST 2.0
A Sen, A Goldstein, S Chakrabarti, N Shang, T Kang, A Yaman, PB Ryan, ...
Journal of the American Medical Informatics Association 25 (3), 239-247, 2018
122018
Evolving plasticity for autonomous learning under changing environmental conditions
A Yaman, G Iacca, DC Mocanu, M Coler, G Fletcher, M Pechenizkiy
Evolutionary Computation, 2020
102020
Similarity-based recommendation of new concepts to a terminology
P Chandar, A Yaman, J Hoxha, Z He, C Weng
AMIA annual symposium proceedings 2015, 386, 2015
102015
Improving (1+ 1) covariance matrix adaptation evolution strategy: A simple yet efficient approach
F Caraffini, G Iacca, A Yaman
AIP Conference Proceedings 2070 (1), 020004, 2019
72019
Structuring Clinical Trial Eligibility Criteria with the Common Data Model
G Levy-Fix, A Yaman, C Weng
Proc of 2015 AMIA Joint Summits for Translational Science, 11-15, 2015
72015
Trend and network analysis of common eligibility features for cancer trials in ClinicalTrials. gov
C Weng, A Yaman, K Lin, Z He
International Conference on Smart Health, 130-141, 2014
72014
Evolutionary algorithm based approach for modeling autonomously trading agents
A Yaman, S Lucci, I Gertner
72014
Multi-strategy differential evolution
A Yaman, G Iacca, M Coler, G Fletcher, M Pechenizkiy
International Conference on the Applications of Evolutionary Computation …, 2017
62017
Learning with delayed synaptic plasticity
A Yaman, G Iacca, DC Mocanu, G Fletcher, M Pechenizkiy
Proceedings of the Genetic and Evolutionary Computation Conference, 152-160, 2019
52019
Presenting the ECO: evolutionary computation ontology
A Yaman, A Hallawa, M Coler, G Iacca
European conference on the applications of evolutionary computation, 603-619, 2017
52017
A framework for knowledge integrated evolutionary algorithms
A Hallawa, A Yaman, G Iacca, G Ascheid
European conference on the applications of evolutionary computation, 653-669, 2017
52017
Distributed embodied evolution over networks
A Yaman, G Iacca
Applied Soft Computing 101, 106993, 2021
32021
Meta-control of social learning strategies
A Yaman, N Bredeche, O Çaylak, JZ Leibo, SW Lee
PLoS computational biology 18 (2), e1009882, 2022
22022
How have cancer clinical trial eligibility criteria evolved over time?
A Yaman, S Chakrabarti, A Sen, C Weng
AMIA Summits on Translational Science Proceedings 2016, 269, 2016
22016
Novelty Producing Synaptic Plasticity
A Yaman, G Iacca, DC Mocanu, G Fletcher, M Pechenizkiy
Genetic and Evolutionary Computation Conference Companion, 93-94, 2020
12020
Smart Health
X Zheng, D Zeng, H Chen, Y Zhang, C Xing, DB Neill
Conference proceedings ICSH, 80, 2014
12014
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