466 citations · 945 across the 39 of their papers we have counts for
4 papers · 1 filter
Bayesian Neural Ordinary Differential Equations
Raj Dandekar, Karen Chung, Vaibhav Dixit +4
Recently, Neural Ordinary Differential Equations has emerged as a powerful framework for modeling physical simulations without explicitly defining the ODEs governing the system, bu…
AutoMat: Accelerated Computational Electrochemical systems Discovery
Emil Annevelink, Rachel Kurchin, Eric Muckley +17
Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and…
Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State Networks
Ranjan Anantharaman, Yingbo Ma, Shashi Gowda +4
Modern design, control, and optimization often requires simulation of highly nonlinear models, leading to prohibitive computational costs. These costs can be amortized by evaluatin…
The Koopman Expectation: An Operator Theoretic Method for Efficient Analysis and Optimization of Uncertain Hybrid Dynamical Systems
Adam R. Gerlach, Andrew Leonard, Jonathan Rogers +1
For dynamical systems involving decision making, the success of the system greatly depends on its ability to make good decisions with incomplete and uncertain information. By lever…