| 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 | 21 | 2019 |
| 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 | 16 | 2019 |
| 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 | 13 | 2018 |
| 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 | 12 | 2018 |
| Evolving plasticity for autonomous learning under changing environmental conditions A Yaman, G Iacca, DC Mocanu, M Coler, G Fletcher, M Pechenizkiy Evolutionary Computation, 2020 | 10 | 2020 |
| 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 | 10 | 2015 |
| 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 | 7 | 2019 |
| 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 | 7 | 2015 |
| 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 | 7 | 2014 |
| Evolutionary algorithm based approach for modeling autonomously trading agents A Yaman, S Lucci, I Gertner | 7 | 2014 |
| Multi-strategy differential evolution A Yaman, G Iacca, M Coler, G Fletcher, M Pechenizkiy International Conference on the Applications of Evolutionary Computation …, 2017 | 6 | 2017 |
| 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 | 5 | 2019 |
| 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 | 5 | 2017 |
| 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 | 5 | 2017 |
| Distributed embodied evolution over networks A Yaman, G Iacca Applied Soft Computing 101, 106993, 2021 | 3 | 2021 |
| Meta-control of social learning strategies A Yaman, N Bredeche, O Çaylak, JZ Leibo, SW Lee PLoS computational biology 18 (2), e1009882, 2022 | 2 | 2022 |
| 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 | 2 | 2016 |
| Novelty Producing Synaptic Plasticity A Yaman, G Iacca, DC Mocanu, G Fletcher, M Pechenizkiy Genetic and Evolutionary Computation Conference Companion, 93-94, 2020 | 1 | 2020 |
| Smart Health X Zheng, D Zeng, H Chen, Y Zhang, C Xing, DB Neill Conference proceedings ICSH, 80, 2014 | 1 | 2014 |
Giovanni IaccaUniversity of TrentoVerified email at unitn.it
