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08/15/2023
An Adaptive Approach for Probabilistic Wind Power Forecasting Based on Meta-Learning
This paper studies an adaptive approach for probabilistic wind power for...
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03/30/2022
One-Step Two-Critic Deep Reinforcement Learning for Inverter-based Volt-Var Control in Active Distribution Networks
A one-step two-critic deep reinforcement learning (OSTC-DRL) approach fo...
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11/01/2021
Combating Noise: Semi-supervised Learning by Region Uncertainty Quantification
Semi-supervised learning aims to leverage a large amount of unlabeled da...
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05/07/2021
A Multivariate Density Forecast Approach for Online Power System Security Assessment
A multivariate density forecast model based on deep learning is designed...
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03/29/2021
Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection
In this paper, we delve into semi-supervised object detection where unla...
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09/28/2020
Fully Automatic Intervertebral Disc Segmentation Using Multimodal 3D U-Net
Intervertebral discs (IVDs), as small joints lying between adjacent vert...
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06/05/2020
Coordinated Transaction Scheduling in Multi-Area Electricity Markets: Equilibrium and Learning
Tie-line scheduling in multi-area power systems in the US largely procee...
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05/30/2019
Hierarchical Structure and Joint Training for Large Scale Semi-supervised Object Detection
Generic object detection is one of the most fundamental and important pr...
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12/06/2016