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Results: 216,847
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  • Ciotta, M., Peyerl, D., & Larizatti Zacharias, L. G. (2023). Effect of the COVID-19 Pandemic on the Brazilian Energy Sector. In D. Peyerl, S. Relva, & V. Da Silva (Eds.), Energy transition in Brazil (pp. 245-258). (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4_15
  • Peyerl, D., Relva, S., & Da Silva, V. (Eds.) (2023). Energy transition in Brazil. (The Latin American Studies Book Series). Springer. https://doi.org/10.1007/978-3-031-21033-4
  • Zhang, J., Cheng, L., Liu, C., Zhao, Z., & Mao, Y. (2023). Cost-aware scheduling systems for real-time workflows in cloud: An approach based on Genetic Algorithm and Deep Reinforcement Learning. Expert Systems With Applications, 234, Article 120972. https://doi.org/10.1016/j.eswa.2023.120972
  • Chen, S., Huang, G., Lin, S., Jiang, W., & Zhao, Z. (2023). Overlapping Community Discovery Algorithm Based on Three-Level Neighbor Node Influence. In Y. Xu, H. Yan, H. Teng, J. Cai, & J. Li (Eds.), Machine Learning for Cyber Security: 4th International Conference, ML4CS 2022, Guangzhou, China, December 2–4, 2022 : proceedings (Vol. II, pp. 335-344). (Lecture Notes in Computer Science; Vol. 13656). Springer. https://doi.org/10.1007/978-3-031-20099-1_28
  • Li, J., Li, J., Xie, C., Liang, Y., Qu, K., Cheng, L., & Zhao, Z. (2023). PipCKG-BS: A Method to Build Cybersecurity Knowledge Graph for Blockchain Systems via the Pipeline Approach. Journal of Circuits, Systems and Computers, 32(16), Article 2350274. https://doi.org/10.1142/S0218126623502742
  • Geng, J., Chen, Z., Wang, Y., Woisetschläger, H., Schimmler, S., Mayer, R., Zhao, Z., & Rong, C. (2023). A Survey on Dataset Distillation: Approaches, Applications and Future Directions. In E. Elkind (Ed.), Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence: IJCAI 2023, Macao, S.A.R, 19-25 August 2023 (Vol. 10, pp. 6610-6618). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2023/741
  • Song, Y., Xin, R., Chen, P., Zhang, R., Chen, J., & Zhao, Z. (2023). Identifying performance anomalies in fluctuating cloud environments: A robust correlative-GNN-based explainable approach. Future Generation Computer Systems, 145, 77-86. https://doi.org/10.1016/j.future.2023.03.020
  • Maier, M., Bartoš, F., & Wagenmakers, E.-J. (2023). Robust Bayesian meta-analysis: Addressing publication bias with model-averaging. Psychological Methods, 28(1), 107-122. https://doi.org/10.1037/met0000405
  • Stanley, T. D., Ioannidis, J. P. A., Maier, M., Doucouliagos, H., Ottema, W. M., & Bartoš, F. (2023). Unrestricted weighted least squares represent medical research better than random effects in 67,308 Cochrane meta-analyses. Journal of Clinical Epidemiology, 157, 53-58. https://doi.org/10.1016/j.jclinepi.2023.03.004
  • Martinková, P., Bartoš, F., & Brabec, M. (2023). Assessing Inter-rater Reliability With Heterogeneous Variance Components Models: Flexible Approach Accounting for Contextual Variables. Journal of Educational and Behavioral Statistics, 48(3), 349-383. https://doi.org/10.3102/10769986221150517
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