Search Results for author: Chao Long

Found 5 papers, 1 papers with code

Extraction of Typical Operating Scenarios of New Power System Based on Deep Time Series Aggregation

no code implementations23 Aug 2024 Zhaoyang Qu, Zhenming Zhang, Nan Qu, Yuguang Zhou, Yang Li, Tao Jiang, Min Li, Chao Long

This study proposed a novel deep time series aggregation scheme (DTSAs) to generate typical operational scenarios, considering the large amount of historical operational snapshot data.

Scheduling Time Series

AvatarVerse: High-quality & Stable 3D Avatar Creation from Text and Pose

1 code implementation7 Aug 2023 Huichao Zhang, Bowen Chen, Hao Yang, Liao Qu, Xu Wang, Li Chen, Chao Long, Feida Zhu, Kang Du, Min Zheng

We present AvatarVerse, a stable pipeline for generating expressive high-quality 3D avatars from nothing but text descriptions and pose guidance.

Text-to-3D-Human Generation

Wind Power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach

no code implementations2 Nov 2022 Yang Li, Ruinong Wang, Yuanzheng Li, Meng Zhang, Chao Long

To handle the data privacy and openness, we propose a forecasting scheme that combines federated learning and deep reinforcement learning (DRL) for ultra-short-term wind power forecasting, called federated deep reinforcement learning (FedDRL).

Deep Reinforcement Learning Federated Learning +4

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