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)

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)

Targeted Demand Response: Formulation, LMP Implications, and Fast Algorithms. - Yufan Zhang; Honglin Wen; Tao Feng; Yize Chen (CoRR, 2022)

Enabling Fast Unit Commitment Constraint Screening via Learning Cost Model. - Xuan He; Honglin Wen; Yufan Zhang; Yize Chen (CoRR, 2022)

Skeleton Sequence and RGB Frame Based Multi-Modality Feature Fusion Network for Action Recognition. - Xiaoguang Zhu; Ye Zhu; Haoyu Wang; Honglin Wen; Yan Yan 002; Peilin Liu (ACM Trans. Multim. Comput. Commun. Appl., 2022)

Fast Constraint Screening for Multi-Interval Unit Commitment. - Xuan He; Jiayu Tian; Yufan Zhang; Honglin Wen; Yize Chen (CDC, 2023)

Probabilistic Wind Power Forecasting with Missing Values via Adaptive Quantile Regression. - Honglin Wen (CoRR, 2023)

Value-oriented Renewable Energy Forecasting for Coordinated Energy Dispatch Problems at Two Stages. - Yufan Zhang; Mengshuo Jia; Honglin Wen; Yuanyuan Shi (CoRR, 2023)

Deriving Loss Function for Value-oriented Renewable Energy Forecasting. - Yufan Zhang; Honglin Wen; Yuexin Bian; Yuanyuan Shi (CoRR, 2023)

Optimal Adaptive Prediction Intervals for Electricity Load Forecasting in Distribution Systems via Reinforcement Learning. - Yufan Zhang; Honglin Wen; Qiuwei Wu; Qian Ai (IEEE Trans. Smart Grid, 2023)

Fast Unit Commitment Constraint Screening with Learning-Based Cost Model. - Xuan He; Honglin Wen; Yufan Zhang; Yize Chen; Danny H. K. Tsang (SmartGridComm, 2024)

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

Improving Sequential Market Clearing via Value-oriented Renewable Energy Forecasting. - Yufan Zhang; Honglin Wen; Yuexin Bian; Yuanyuan Shi (CoRR, 2024)

Efficient Unit Commitment Constraint Screening under Uncertainty. - Xuan He; Honglin Wen; Yufan Zhang; Yize Chen; Danny H. K. Tsang (CoRR, 2024)

A Contextual Bandit Approach for Value-Oriented Prediction Interval Forecasting. - Yufan Zhang; Honglin Wen; Qiuwei Wu (IEEE Trans. Smart Grid, 2024)

Value-oriented forecast reconciliation for renewables in electricity markets. - Honglin Wen; Pierre Pinson (CoRR, 2025)

Toward Value-Oriented Renewable Energy Forecasting: An Iterative Learning Approach. - Yufan Zhang; Mengshuo Jia; Honglin Wen; Yuexin Bian; Yuanyuan Shi (IEEE Trans. Smart Grid, 2025)