Ginar: An end-to-end multivariate time series forecasting model suitable for variable missing
Multivariate time series forecasting (MTSF) is crucial for decision-making to precisely
forecast the future values/trends, based on the complex relationships identified from …
forecast the future values/trends, based on the complex relationships identified from …
GMP-AR: Granularity Message Passing and Adaptive Reconciliation for Temporal Hierarchy Forecasting
Time series forecasts of different temporal granularity are widely used in real-world
applications, eg, sales prediction in days and weeks for making different inventory plans …
applications, eg, sales prediction in days and weeks for making different inventory plans …
Graph-based Time Series Clustering for End-to-End Hierarchical Forecasting
A Cini, D Mandic, C Alippi - ar** Insights into Anomalies in Hierarchically Aggregated …
L Zólyomi - 2024 - aaltodoc.aalto.fi
The proliferation of time series data across industrial domains has made anomaly detection
a critical task for ensuring operational efficiency and reliability. This thesis explores two …
a critical task for ensuring operational efficiency and reliability. This thesis explores two …