Short-term load forecasting using a long short-term memory network. - Chang Liu; Zhijian Jin; Jie Gu 005; Robert Caiming Qiu (ISGT Europe, 2017)

Probabilistic Wind Power Forecasting via Bayesian Deep Learning Based Prediction Intervals. - Honglin Wen; Jie Gu 005; Jinghuan Ma; Zhijian Jin (INDIN, 2019)

Unearthing Details of Time Series of Load: A Dual-scale Input Structured LSTM Approach. - Lyuzerui Yuan; Jinghuan Ma; Jie Gu 005; Honglin Wen; Zhijian Jin (e-Energy, 2020)

Dimensional Pricing Based on Dynamism of Load. - Jinghuan Ma; Jie Gu 005; Zhijian Jin (CoRR, 2020)

Two-Layer Transfer-Learning-Based Architecture for Short-Term Load Forecasting. - Long Cai; Jie Gu 005; Zhijian Jin (IEEE Trans. Ind. Informatics, 2020)

Probabilistic Load Forecasting via Neural Basis Expansion Model Based Prediction Intervals. - Honglin Wen; Jie Gu 005; Jinghuan Ma; Lyuzerui Yuan; Zhijian Jin (IEEE Trans. Smart Grid, 2021)

Wind energy forecasting with missing values within a fully conditional specification framework. - Honglin Wen; Pierre Pinson; Jie Gu 005; Zhijian Jin (CoRR, 2022)

Continuous and Distribution-free Probabilistic Wind Power Forecasting: A Conditional Normalizing Flow Approach. - Honglin Wen; Pierre Pinson; Jinghuan Ma; Jie Gu 005; Zhijian Jin (CoRR, 2022)

Tackling Missing Values in Probabilistic Wind Power Forecasting: A Generative Approach. - Honglin Wen; Pierre Pinson; Jie Gu 005; Zhijian Jin (CoRR, 2024)