29 citations · 89 across the 13 of their papers we have counts for
5 papers · 1 filter
Wind Power Scenario Generation Using Graph Convolutional Generative Adversarial Network
Young-ho Cho, Shaohui Liu, Duehee Lee +1
Generating wind power scenarios is very important for studying the impacts of multiple wind farms that are interconnected to the grid. We develop a graph convolutional generative a…
Appliance Level Short-term Load Forecasting via Recurrent Neural Network
Yuqi Zhou, Arun Sukumaran Nair, David Ganger +3
Accurate load forecasting is critical for electricity market operations and other real-time decision-making tasks in power systems. This paper considers the short-term load forecas…
Graph Convolutional Network with Generalized Factorized Bilinear Aggregation
Hao Zhu, Piotr Koniusz
Although Graph Convolutional Networks (GCNs) have demonstrated their power in various applications, the graph convolutional layers, as the most important component of GCN, are stil…
Multi-agent Trajectory Prediction with Fuzzy Query Attention
Nitin Kamra, Hao Zhu, Dweep Trivedi +2
Trajectory prediction for scenes with multiple agents and entities is a challenging problem in numerous domains such as traffic prediction, pedestrian tracking and path planning. W…
Using Graph Neural Networks for Mass Spectrometry Prediction
Hao Zhu, Liping Liu, Soha Hassoun
Detecting and quantifying products of cellular metabolism using Mass Spectrometry (MS) has already shown great promise in many biological and biomedical applications. The biggest c…