128 citations · 603 across the 20 of their papers we have counts for
21 papers
Manifold learning for parameter reduction
Alexander Holiday, Mahdi Kooshkbaghi, Juan M. Bello-Rivas +3
Large scale dynamical systems (e.g. many nonlinear coupled differential equations) can often be summarized in terms of only a few state variables (a few equations), a trait that re…
Coarse-Grained Descriptions of Dynamics for Networks with both Intrinsic and Structural Heterogeneities
Tom Bertalan, Yan Wu, Carlo Laing +2
Finding accurate reduced descriptions for large, complex, dynamically evolving networks is a crucial enabler to their simulation, analysis, and, ultimately, design. Here we propose…
iMapD: intrinsic Map Dynamics exploration for uncharted effective free energy landscapes
Eliodoro Chiavazzo, Ronald R. Coifman, Roberto Covino +4
We describe and implement iMapD, a computer-assisted approach for accelerating the exploration of uncharted effective Free Energy Surfaces (FES), and more generally for the extract…
Data-Driven Reduction for Multiscale Stochastic Dynamical Systems
Carmeline J. Dsilva, Ronen Talmon, C. William Gear +2
Multiple time scale stochastic dynamical systems are ubiquitous in science and engineering, and the reduction of such systems and their models to only their slow components is ofte…
On the acceleration of spatially distributed agent-based computations: a patch dynamics scheme
Ping Liu, Giovanni Samaey, C. William Gear +1
In recent years, individual-based/agent-based modeling has been applied to study a wide range of applications, ranging from engineering problems to phenomena in sociology, economic…
Reduced models in chemical kinetics via nonlinear data-mining
Eliodoro Chiavazzo, C. William Gear, Carmeline J. Dsilva +2
The adoption of detailed mechanisms for chemical kinetics often poses two types of severe challenges: First, the number of degrees of freedom is large; and second, the dynamics is…