activity
20192023
collaborators

6 papers

cs.LG2023

Infinite forecast combinations based on Dirichlet process

Yinuo Ren, Feng Li, Yanfei Kang +1

Forecast combination integrates information from various sources by consolidating multiple forecast results from the target time series. Instead of the need to select a single opti…

cs.AI2023

Probabilistic Forecast Reconciliation with Kullback-Leibler Divergence Regularization

Guanyu Zhang, Feng Li, Yanfei Kang

As the popularity of hierarchical point forecast reconciliation methods increases, there is a growing interest in probabilistic forecast reconciliation. Many studies have utilized…

stat.ME2022

Optimal reconciliation with immutable forecasts

Bohan Zhang, Yanfei Kang, Anastasios Panagiotelis +1

The practical importance of coherent forecasts in hierarchical forecasting has inspired many studies on forecast reconciliation. Under this approach, so-called base forecasts are p…

stat.ME2020

Forecast with Forecasts: Diversity Matters

Yanfei Kang, Wei Cao, Fotios Petropoulos +1

Forecast combinations have been widely applied in the last few decades to improve forecasting. Estimating optimal weights that can outperform simple averages is not always an easy…

stat.ML2019

Forecasting with time series imaging

Xixi Li, Yanfei Kang, Feng Li

Feature-based time series representations have attracted substantial attention in a wide range of time series analysis methods. Recently, the use of time series features for foreca…

stat.ML2019

GRATIS: GeneRAting TIme Series with diverse and controllable characteristics

Yanfei Kang, Rob J Hyndman, Feng Li

The explosion of time series data in recent years has brought a flourish of new time series analysis methods, for forecasting, clustering, classification and other tasks. The evalu…