8 citations · 8 across the 1 of their papers we have counts for
3 papers
cs.SI2019★ 8 cited
Deep Generative Graph Distribution Learning for Synthetic Power Grids
Mahdi Khodayar, Jianhui Wang, Zhaoyu Wang
Power system studies require the topological structures of real-world power networks; however, such data is confidential due to important security concerns. Thus, power grid synthe…
cs.LG2018
Convolutional Graph Auto-encoder: A Deep Generative Neural Architecture for Probabilistic Spatio-temporal Solar Irradiance Forecasting
Mahdi Khodayar, Saeed Mohammadi, Mohammad Khodayar +2
Machine Learning on graph-structured data is an important and omnipresent task for a vast variety of applications including anomaly detection and dynamic network analysis. In this…
cs.LG2018
Energy Disaggregation via Deep Temporal Dictionary Learning
Mahdi Khodayar, Jianhui Wang, Zhaoyu Wang
This paper addresses the energy disaggregation problem, i.e. decomposing the electricity signal of a whole home to its operating devices. First, we cast the problem as a dictionary…