Applications
Application&Citation Papers
Up to now, this open-source Python library PyPop7 has been used/cited (at least) in the following papers (note that the below list is actively updated):
[cited] indicates that PyPop7 has been cited but not used by the corresponding paper.
[used] indicates that PyPop7 has been used (but not cited in reference) by the corresponding paper.
13: Miranda, P.B., Giráldez-Cru, J., Silva-Filho, M.W., Zarco, C. and Cordón, O., 2024, June. Learning agents’ behavioral patterns in agent-Based modeling by means of evolutionary algorithms. In IEEE Congress on Evolutionary Computation (pp. 1-8). IEEE.
12: Ma, Z., Chen, J., Guo, H. and Gong, Y.J., 2024. Neural Exploratory Landscape Analysis. arXiv preprint arXiv:2408.10672. [used&cited]
South China University of Technology
11: Pinchuk, M., Kirgizov, G., Yamshchikova, L., Nikitin, N., Deeva, I., Shakhkyan, K., Borisov, I., Zharkov, K. and Kalyuzhnaya, A., 2024, July. GOLEM: Flexible Evolutionary Design of Graph Representations of Physical and Digital Objects. In Proceedings of Annual Genetic and Evolutionary Computation Conference Companion (pp. 1668-1675). ACM. [cited]
ITMO University
10: Vodopija, A., Cork, J.N. and Filipič, B., 2024, July. The Lunar Lander Landing Site Selection Benchmark Reexamined: Problem Characterization and Algorithm Performance. In Proceedings of Annual Genetic and Evolutionary Computation Conference (pp. 1381-1389). ACM. [used&cited]
Jozef Stefan Institute + Jozef Stefan International Postgraduate School
JADE
9: Bailo, R., Barbaro, A., Gomes, S.N., Riedl, K., Roith, T., Totzeck, C. and Vaes, U., 2024. CBX: Python and Julia Packages for Consensus-based Interacting Particle Methods. arXiv preprint arXiv:2403.14470. [cited]
University of Oxford + Technische Universiteit Delft + University of Warwick + Technical University of Munich + Munich Center for Machine Learning + Deutsches Elektronen-Synchrotron DESY + University of Wuppertal + Inria + Ecole des Ponts
8: Ma, Z., Guo, H., Chen, J., Peng, G., Cao, Z., Ma, Y. and Gong, Y.J., 2024. LLaMoCo: Instruction Tuning of Large Language Models for Optimization Code Generation. arXiv preprint arXiv:2403.01131. [used&cited]
South China University of Technology + Singapore Management University + Nanyang Technological University
7: Zhang, Z., Wei, Y. and Sui, Y., 2024. An Invariant Information Geometric Method for High-Dimensional Online Optimization. arXiv preprint arXiv:2401.01579. [used&cited]
Tsinghua University
6: Yu, L., Chen, Q., Lin, J. and He, L., 2023. Black-box Prompt Tuning for Vision-Language Model as a Service. Proceedings of International Joint Conference on Artificial Intelligence (pp. 1686-1694). IJCAI. [used]
East China Normal University
5: Lee, Y., Lee, K., Hsu, D., Cai, P. and Kavraki, L.E., 2023. The Planner Optimization Problem: Formulations and Frameworks. arXiv preprint arXiv:2303.06768. [used&cited]
Rice University + Shanghai Jiao Tong University + National University of Singapore
4: Duan, Q., Shao, C., Zhou, G., Zhang, M., Zhao, Q. and Shi, Y., 2023. Distributed Evolution Strategies with Multi-Level Learning for Large-Scale Black-Box Optimization. arXiv preprint arXiv:2310.05377. [used]
Duan, Q., Shao, C., Zhou, G., Zhang, M., Zhao, Q. and Shi, Y., 2024. Distributed Evolution Strategies With Multi-Level Learning for Large-Scale Black-Box Optimization. IEEE Transactions on Parallel & Distributed Systems, 35(11), pp.2087-2101.
Harbin Institute of Technology + Southern University of Science and Technology + University of Technology Sydney + University of Warwick
3: Duan, Q., Shao, C., Zhou, G., Yang, H., Zhao, Q. and Shi, Y., 2023. Cooperative Coevolution for Non-Separable Large-Scale Black-Box Optimization: Convergence Analyses and Distributed Accelerations. arXiv preprint arXiv:2304.05020. [used]
Harbin Institute of Technology + Southern University of Science and Technology + University of Technology Sydney
2: Duan, Q., Zhou, G., Shao, C., Yang, Y. and Shi, Y., 2022. Collective Learning of Low-Memory Matrix Adaptation for Large-Scale Black-Box Optimization. In International Conference on Parallel Problem Solving from Nature (pp. 281-294). Springer, Cham. [used, this research paper entered the nomination list of the Best Paper Award on PPSN-2022]
Harbin Institute of Technology + Southern University of Science and Technology + University of Technology Sydney
1: Duan, Q., Zhou, G., Shao, C., Yang, Y. and Shi, Y., 2022, July. Distributed Evolution Strategies for Large-Scale Optimization. In Proceedings of ACM Genetic and Evolutionary Computation Conference Companion (pp. 395-398). ACM. [used]
Harbin Institute of Technology + Southern University of Science and Technology + University of Technology Sydney
Open-Source Cases
Till now, this Python library PyPop7 has been used (at least) in the following open-source projects:
15 [2024]: https://github.com/GMC-DRL/Neur-ELA
FCMAES + SEPCMAES + RMES + CMAES
14 [2024]: https://github.com/nikivanstein/LLaMEA
13: https://github.com/AmitDIRTYC0W/neuronveil-mnist-train (2024)
CLPSO + GL25 + SHADE + JADE + LEP
12: https://pypi.org/project/advanced-global-optimizers/ (2024)
11: https://github.com/aiboxlab/evolutionary-abm-calibration (2024)
10: https://github.com/Echozqn/llm [https://github.com/Echozqn/llm/tree/main/collie/examples/alpaca/eda] (2024)
Unfortunately, this open-source project is not openly accessible now.
9: https://github.com/BruthYU/BPT-VLM (2023)
8: https://github.com/opoframework/opof [online docs: https://opof.kavrakilab.org/] (2023)
7: https://github.com/pyanno4rt/pyanno4rt [online docs: https://pyanno4rt.readthedocs.io/en/latest/] (2023)
Tim Ortkamp: Scientific Computing Center, Karlsruhe Institute of Technology (KIT) + Medical Physics in Radiation Oncology, German Cancer Research Center (DKFZ) + Helmholtz Information and Data Science School for Health
LMCMA + LMMAES
6: https://github.com/TUIlmenauAMS/BlackBoxOptimizerSPcomparison (2023)
4: https://github.com/jeancroy/RP-fit (2023)
3: https://github.com/moesio-f/py-abm-public (2023)
Unfortunately, this open-source project is not openly accessible now.
2: https://github.com/Evolutionary-Intelligence/M-DES (2023)
1: https://github.com/Evolutionary-Intelligence/dpop7 (2023)
This is a parallel/distributed extension to PyPop7 (now actively developed).
Introduction Cases
For other introductions/coverage to this open-source library PyPop7, refer to e.g.:
Praises
All of the following praises come from online states. We appreciate very much for these unstinting praises, given that we do not have an interest relationship with all of them: