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Dynamical Systems
Emergent spaces for coupled oscillators
Systems of coupled dynamical units (e.g., oscillators or neurons) are known to exhibit complex, emergent behaviors that may be …
Thomas N. Thiem
,
Mahdi Kooshkbaghi
,
Tom Bertalan
,
Carlo R. Liang
,
Ioannis G. Kevrekidis
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Manifold learning for organizing unstructured sets of process observations
Data mining is routinely used to organize ensembles of short temporal observations so as to reconstruct useful, low-dimensional …
Felix Dietrich
,
Mahdi Kooshkbaghi
,
Erik M. Bolt
,
Ioannis G. Kevrekidis
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Coarse-scale PDEs from fine-scale observations via machine learning
Complex spatiotemporal dynamics of physicochemical processes are often modeled at a microscopic level (through, e.g., atomistic, …
Seungjoon Lee
,
Mahdi Kooshkbaghi
,
Konstantinos Spiliotis
,
Constantinos I. Siettos
,
Ioannis G. Kevrekidis
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Manifold learning for parameter reduction
Large scale dynamical systems (e.g. many nonlinear coupled differential equations) can often be summarized in terms of only a few state …
Alexander Holiday
,
Mahdi Kooshkbaghi
,
Juan M. Bello-Rivas
,
C. William Gear
,
Antonios Zagaris
,
Ioannis G. Kevrekidis
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n-Heptane/air combustion in perfectly stirred reactors: Dynamics, bifurcations and dominant reactions at critical conditions
The dynamics of n-heptane/air mixtures in perfectly stirred reactors (PSR) is investigated systematically using bifurcation and …
Mahdi Kooshkbaghi
,
Christos E. Frouzakis
,
Konstantinos Boulouchos
,
Ilya V. Karlin
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On the model reduction for chemical and physical kinetics
The need to design of efficient combustion systems with minimal emissions of pollutants has led to the development of large detailed …
Mahdi Kooshkbaghi
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