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Generating Data using Monte Carlo Dropout., , , and . ICCP, page 509-515. IEEE, (2019)Tuning Logstash Garbage Collection for High Throughput in a Monitoring Platform., and . SYNASC, page 359-365. IEEE, (2016)Multiple Imputation for Biomedical Data using Monte Carlo Dropout Autoencoders., , , and . CoRR, (2020)A novel entropy of intuitionistic fuzzy sets based on similarity and its application in finance., , , and . J. Intell. Fuzzy Syst., 43 (4): 3899-3909 (2022)Auto-scaling for a Streaming Architecture with Fuzzy Deep Reinforcement Learning., , and . Euro-Par Workshops, volume 11997 of Lecture Notes in Computer Science, page 476-488. Springer, (2019)An Ensemble Learning Approach for Credit Scoring Problem: A Case Study of Taiwan Default Credit Card Dataset., , , and . MCO, volume 363 of Lecture Notes in Networks and Systems, page 283-292. Springer, (2021)Prediction Uncertainty Estimation for Hate Speech Classification., , , , and . SLSP, volume 11816 of Lecture Notes in Computer Science, page 286-298. Springer, (2019)Toward on-Line Predictive Models for Forecasting Workload in Clouds.. SYNASC, page 260-265. IEEE, (2018)Investigation on new Mel frequency cepstral coefficients features and hyper-parameters tuning technique for bee sound recognition., , , , and . Soft Comput., 27 (9): 5873-5892 (May 2023)