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This paper introduces pmuGE (phasor measurement unit Generator of Events), one of the first data-driven generative model for power system event data. We have trained this model on thousands of actual events and created a dataset denoted pmuBAGE (the
Externí odkaz:
http://arxiv.org/abs/2210.14204
We present pmuGE (phasor measurement unit Generator of Events), one of the first data-driven generative model for power system event data. We have trained this model on thousands of actual events and created a dataset denoted pmuBAGE (the Benchmarkin
Externí odkaz:
http://arxiv.org/abs/2204.01095
Autor:
Bauer, Franz, Knights, Antony M., Griffin, John N., Hanley, Mick E., Foggo, Andy, Brown, Austin, Jones, Emma, Firth, Louise B.
Publikováno v:
In Science of the Total Environment 15 August 2024 938
Autor:
Bauer, Franz, Knights, Antony M., Hanley, Mick E., Griffin, John N., Foggo, Andy, Brown, Austin, Firth, Louise B.
Publikováno v:
In Marine Pollution Bulletin May 2024 202
Autor:
Tasker, Samuel J.L., Foggo, Andrew, Scheers, Kevin, van der Loop, Janneke, Giordano, Salvatore, Bilton, David T.
Publikováno v:
In Science of the Total Environment 25 February 2024 913
Publikováno v:
In Nurse Education in Practice January 2024 74
Online power system event identification and classification is crucial to enhancing the reliability of transmission systems. In this paper, we develop a deep neural network (DNN) based approach to identify and classify power system events by leveragi
Externí odkaz:
http://arxiv.org/abs/2011.06718
Autor:
Foggo, Brandon, Yu, Nanpeng
We derive the closed-form expression of the maximum mutual information - the maximum value of $I(X;Z)$ obtainable via training - for a broad family of neural network architectures. The quantity is essential to several branches of machine learning the
Externí odkaz:
http://arxiv.org/abs/2006.06037
Algorithmic fairness is receiving significant attention in the academic and broader literature due to the increasing use of predictive algorithms, including those based on artificial intelligence. One benefit of this trend is that algorithm designers
Externí odkaz:
http://arxiv.org/abs/2001.07864
Autor:
Foggo, James G., Gosnell, Rachael
Publikováno v:
Naval War College Review, 2022 Jul 01. 75(3), 13-36.
Externí odkaz:
https://www.jstor.org/stable/48732016