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Time Series Forecasting of COVID-19 Cases in Brazil with GNN and Mobility Networks., , , , and . BRACIS (3), volume 14197 of Lecture Notes in Computer Science, page 361-375. Springer, (2023)Correlations Between Epidemiological Time Series Forecasting and Influence Regions of Brazilian Cities., , , , and . GEOINFO, page 340-345. MCTI/INPE, (2023)Comparative protein analysis of the chitin metabolic pathway in extant organisms: A complex network approach., , , , , , , , and . Biosyst., 101 (1): 59-66 (2010)Towards generating a traffic slowness geospatial dataset of São Paulo city., , and . GEOINFO, page 411-416. MCTIC/INPE, (2022)Rain-related Tweets in flooding days: a brief analysis on Tamanduateí river basin., , , , and . GEOINFO, page 378-383. MCTIC/INPE, (2022)Challenges and perspectives of innovative digital ecosystems designed to monitor and warn natural disasters in Brazil., , , , , , , , , and . MEDES, page 254-261. ACM, (2013)A convolutional LSTM neural network for precipitation nowcasting based on weather radar data., , , and . GEOINFO, page 384-388. MCTIC/INPE, (2022)Comparando o Custo Temporal Para Diferentes Métodos de Cálculo de Comunicabilidade em Redes Viárias., , , and . GEOINFO, page 471-476. MCTI/INPE, (2023)Robustness analysis in an inter-cities mobility network: modeling municipal, state and federal initiatives as failures and attacks., , , and . CoRR, (2020)Statistical analysis of a spatially explicit hydrological forecasting model using remote sensing of the atmosphere., , and . GEOINFO, page 223-228. MCTIC/INPE, (2022)