Evaluating Linear Models as a Baseline for Time Series Imputation. - Rebecca Salles; Eduardo Bezerra 002; Jorge de Abreu Soares; Eduardo S. Ogasawara (SBBD (Short Papers), 2015)

Evaluating temporal aggregation for predicting the sea surface temperature of the Atlantic Ocean. - Rebecca Salles; Patricia Mattos; Ana-Maria Dubois Iorgulescu; Eduardo Bezerra 002; Leonardo Silva de Lima; Eduardo S. Ogasawara (Ecol. Informatics, 2016)

A framework for benchmarking machine learning methods using linear models for univariate time series prediction. - Rebecca Salles; Laura Assis; Gustavo Paiva Guedes; Eduardo Bezerra 002; Fábio Porto 001; Eduardo S. Ogasawara (IJCNN, 2017)

A Conceptual Vision Toward the Management of Machine Learning Models. - Daniel Nascimento Ramos da Silva; Adolfo Simões; Carlos Cardoso; Douglas E. M. de Oliveira; João N. Rittmeyer; Klaus Wehmuth; Hermano Lustosa; Rafael S. Pereira 001; Yania Molina Souto; Luciana E. G. Vignoli; Rebecca Salles; Heleno de S. C. Jr; et al. (ER Forum/Posters/Demos, 2019)

Modelo Autorregressivo de Integração Adaptativa. - Arthur Ronald; Rebecca Salles; Kele T. Belloze; Dayse H. Pastore; Eduardo S. Ogasawara (SBBD, 2019)

Nonstationary time series transformation methods: An experimental review. - Rebecca Salles; Kele T. Belloze; Fábio Porto 001; Pedro H. Gonzalez; Eduardo S. Ogasawara (Knowl. Based Syst., 2019)

Harbinger: Um framework para integração e análise de métodos de detecção de eventos em séries temporais. - Rebecca Salles; Luciana E. G. Escobar; Laís Baroni; Roccio Zorrilla; Artur Ziviani; Vincius Kreischer; Flávia Coimbra Delicato; Paulo F. Pires; Luciano Maia; Rafaelli Coutinho; Laura Assis; Eduardo S. Ogasawara (SBBD, 2020)

Estimation of COVID-19 under-reporting in Brazilian States through SARI. - Balthazar Paixão; Laís Baroni; Rebecca Salles; Luciana E. G. Escobar; Carlos de Sousa; Marcel Pedroso; Raphael de Freitas Saldanha; Rafaelli Coutinho; Fábio Porto 001; Eduardo S. Ogasawara (CoRR, 2020)

An analysis of malaria in the Brazilian Legal Amazon using divergent association rules. - Laís Baroni; Rebecca Salles; Samella Salles; Gustavo Paiva Guedes; Fábio Porto 001; Eduardo Bezerra 002; Christovam Barcellos; Marcel Pedroso; Eduardo S. Ogasawara (J. Biomed. Informatics, 2020)

Requirements for an Ontology of Digital Twins. - Claudio Daniel Tenorio de Barros; Rebecca Salles; Eduardo S. Ogasawara; Giancarlo Guizzardi; Fábio Porto 001 (SEMANTiCS (Posters & Demos), 2021)

Evaluating Temporal Bias in Time Series Event Detection Methods. - Luciana E. G. Escobar; Rebecca Salles; Janio Lima; Cristiane Gea; Laís Baroni; Artur Ziviani; Paulo F. Pires; Flávia Coimbra Delicato; Rafaelli Coutinho; Laura Assis; Eduardo S. Ogasawara (J. Inf. Data Manag., 2021)

Estimation of COVID-19 Under-Reporting in the Brazilian States Through SARI. - Balthazar Paixão; Laís Baroni; Marcel Pedroso; Rebecca Salles; Luciana E. G. Escobar; Carlos de Sousa; Raphael de Freitas Saldanha; Jorge Soares 001; Rafaelli Coutinho; Fábio Porto 001; Eduardo S. Ogasawara (New Gener. Comput., 2021)

Forward and Backward Inertial Anomaly Detector: A Novel Time Series Event Detection Method. - Janio Lima; Rebecca Salles; Fábio Porto 001; Rafaelli Coutinho; Pedro Alpis; Luciana E. G. Escobar; Esther Pacitti; Eduardo S. Ogasawara (IJCNN, 2022)

Towards Robust Cluster-Based Hyperparameter Optimization. - Leonardo Izaú; Mariana Fortes; Vítor Ribeiro; Celso Marques; Carla Oliveira; Eduardo Bezerra 002; Fábio Porto 001; Rebecca Salles; Eduardo S. Ogasawara (SBBD, 2022)

TSPred: A framework for nonstationary time series prediction. - Rebecca Salles; Esther Pacitti; Eduardo Bezerra 002; Fábio Porto 001; Eduardo S. Ogasawara (Neurocomputing, 2022)

Machine Learning Approaches to Extreme Weather Events Forecast in Urban Areas: Challenges and Initial Results. - Fábio Porto 001; Mariza Ferro; Eduardo S. Ogasawara; Thiago Moeda; Claudio Daniel Tenorio de Barros; Anderson Chaves da Silva; Rocío Zorrilla; Rafael Silva Pereira; Rafaela Nascimento Castro; João Victor Silva; Rebecca Salles; Augusto José Fonseca; et al. (Supercomput. Front. Innov., 2022)

Data Science Platform Applied to Health in Contribution to the Brazilian Unified Health System. - Marcel Pedroso; Rebecca Salles; Raphael de Freitas Saldanha; Vinicius Kreischer de Almeida; Gabriel Souto; Balthazar Paixão; Sérgio Ricardo de Borba Cruz; Carlos Cardoso; Víctor Ribeiro; Raquel Gritz; Carmen Bonifácio; Matheus Miloski; et al. (VLDB Workshops, 2023)

SoftED: Metrics for Soft Evaluation of Time Series Event Detection. - Rebecca Salles; Janio Lima; Rafaelli Coutinho; Esther Pacitti; Florent Masseglia; Reza Akbarinia; Chao Chen 007; Jonathan M. Garibaldi; Fábio Porto 001; Eduardo S. Ogasawara (CoRR, 2023)

TSPredIT: Integrated Tuning of Data Preprocessing and Time Series Prediction Models. - Rebecca Salles; Esther Pacitti; Eduardo Bezerra 002; Celso Marques; Carla Pacheco; Carla Oliveira; Fábio Porto 001; Eduardo S. Ogasawara (Trans. Large Scale Data Knowl. Centered Syst., 2023)

Matching Detections to Events in Time Series. - Michel Reis; Rebecca Salles; Geraldo Xexéo; Rafaelli Coutinho; Eduardo S. Ogasawara (SBBD, 2024)

SoftED: Metrics for soft evaluation of time series event detection. - Rebecca Salles; Janio Lima; Michel Reis; Rafaelli Coutinho; Esther Pacitti; Florent Masseglia; Reza Akbarinia; Chao Chen 007; Jonathan M. Garibaldi; Fábio Porto 001; Eduardo S. Ogasawara (Comput. Ind. Eng., 2024)

Fuzzy-Based Ensemble Method for Robust Concept Drift Detection in Multivariate Time Series. - Lucas Giusti Tavares; Janio Lima; Matheus Melo; Chao Chen 007; Jon Garibaldi; Gabriel dos Santos Scatena; Anna Helena Reali Costa; Edson Satoshi Gomi; Rebecca Salles; Esther Pacitti; Ismael H. F. dos Santos; Isabela Guimarães Siqueira; et al. (IJCNN, 2025)

Scalable and accurate online multivariate anomaly detection. - Rebecca Salles; Benoit Lange; Reza Akbarinia; Florent Masseglia; Eduardo S. Ogasawara; Esther Pacitti (Inf. Syst., 2025)