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08/15/2023
Graph-Structured Kernel Design for Power Flow Learning using Gaussian Processes
This paper presents a physics-inspired graph-structured kernel designed ...
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12/04/2021
DNN-based Policies for Stochastic AC OPF
A prominent challenge to the safe and optimal operation of the modern po...
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04/02/2021
Exponential Reduction in Sample Complexity with Learning of Ising Model Dynamics
The usual setting for learning the structure and parameters of a graphic...
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02/18/2021
Learning Continuous Exponential Families Beyond Gaussian
We address the problem of learning of continuous exponential family dist...
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06/21/2020
Learning of Discrete Graphical Models with Neural Networks
Graphical models are widely used in science to represent joint probabili...
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05/04/2020
Tractable learning in under-excited power grids
Estimating the structure of physical flow networks such as power grids i...
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02/02/2019
Efficient Learning of Discrete Graphical Models
Graphical models are useful tools for describing structured high-dimensi...
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06/21/2016
Graphical Models for Optimal Power Flow
Optimal power flow (OPF) is the central optimization problem in electric...
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05/24/2016
Interaction Screening: Efficient and Sample-Optimal Learning of Ising Models
We consider the problem of learning the underlying graph of an unknown I...
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02/05/2016