75 citations · 208 across the 12 of their papers we have counts for
12 papers
Bayesian hypergraph inference from scarce and noisy dynamical observations
Katerina Tang, Vivek Srikrishnan, Jackson Kulik
Inferring higher-order interaction structure from observations of dynamics is a central challenge in complex systems, particularly when data are scarce, noisy, or concentrated in l…
Identification of pressure points in modern power systems using transfer entropy
Katerina Tang, M. Vivienne Liu, C. Lindsay Anderson +1
Integration of variable energy resources -- e.g., solar, wind, and hydro -- and end-use electrification increase modern energy systems' weather-dependence. Identifying critical inf…
Graph Neural Ordinary Differential Equations for Coarse-Grained Socioeconomic Dynamics
James Koch, Pranab Roy Chowdhury, Heng Wan +4
We present a data-driven machine-learning approach for modeling space-time socioeconomic dynamics. Through coarse-graining fine-scale observations, our modeling framework simplifie…
Quantifying the multi-scale and multi-resource impacts of large-scale adoption of renewable energy sources
Elnaz Kabir, Vivek Srikrishnan, M. Vivienne Liu +2
The variability and intermittency of renewable energy sources pose several challenges for power systems operations, including energy curtailment and price volatility. In power syst…
Heterogeneous Vulnerability of Zero-Carbon Power Grids under Climate-Technological Changes
M. Vivienne Liu, Vivek Srikrishnan, Kenji Doering +3
The transition to decarbonized energy systems has become a priority globally to mitigate carbon emissions and, therefore, climate change. However, the vulnerabilities of zero-carbo…
Emulation methods and adaptive sampling increase the efficiency of sensitivity analysis for computationally expensive models
Haochen Ye, Robert E. Nicholas, Vivek Srikrishnan +1
Models with high-dimensional parameter spaces are common in many applications. Global sensitivity analyses can provide insights on how uncertain inputs and interactions influence t…