EVENTO
Comparative Study of Transformers in Spatiotemporal Precipitation Forecasting
Tipo de evento: Defesa de Dissertação de Mestrado
Precipitation is a meteorological phenomenon that plays a fundamental role in numerous human activities, which creates the need to develop models to predict it. Deep Learning Models (DLMs) have excelled in various time series prediction tasks. Among these DLMs, it is worth highlighting the Transformer based models, which havestood out with their attention mechanisms. This study aims to investigate the applicability of transformer models, compared to classical models for spatiotemporal precipitation prediction, highlighting how attention mechanisms detect spatiotemporal patterns.Para assistir acesse:meet.google.com/zui-dedv-tjh
Data Início: 28/08/2024 Hora: 14:00 Data Fim: 28/08/2024 Hora: 17:00
Local: LNCC - Laboratório Nacional de Computação Ciêntifica - Virtual
Aluno: Mauro Sérgio dos Santos Moura - - LNCC
Orientador: Fabio André Machado Porto - Laboratório Nacional de Computação Científica - LNCC
Participante Banca Examinadora: Eduardo Bezerra da Silva - CEFET - RJ Fabio André Machado Porto - Laboratório Nacional de Computação Científica - LNCC Gilson Antônio Giraldi - Laboratório Nacional de Computação Científica - LNCC José Antônio de Fernandes Macedo - UFC -
Suplente Banca Examinadora: Pablo Javier Blanco - Laboratório Nacional de Computação Científica - LNCC
