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Found 7 papers, 3 papers with code
Anomaly detection in dynamic networks
Detecting anomalies from a series of temporal networks has many applications, including road accidents in transport networks and suspicious events in social networks.
Forecast combinations: an over 50-year review
Forecast combinations have flourished remarkably in the forecasting community and, in recent years, have become part of the mainstream of forecasting research and activities.
LoMEF: A Framework to Produce Local Explanations for Global Model Time Series Forecasts
Global Forecasting Models (GFM) that are trained across a set of multiple time series have shown superior results in many forecasting competitions and real-world applications compared with univariate forecasting approaches.
A Look at the Evaluation Setup of the M5 Forecasting Competition
Scale normalization of the M5 error measure results in less stability than other scale-free errors.
Computationally Efficient Learning of Statistical Manifolds
By exploiting the connection between Hellinger/total variation distance for discrete distributions and the L2/L1 norm, we demonstrate that the proposed distance estimators, combined with approximate nearest neighbor searching, could largely improve the computational efficiency with little to no loss in the accuracy of manifold embedding.
Modern strategies for time series regression
This paper discusses several modern approaches to regression analysis involving time series data where some of the predictor variables are also indexed by time.
Model selection in reconciling hierarchical time series
However, when dealing with hierarchical time series, apart from selecting the most appropriate forecasting model, forecasters have also to select a suitable method for reconciling the base forecasts produced for each series to make sure they are coherent.
