Slow Invariant Manifolds of Fast-Slow Systems of ODEs with Physics-Informed Neural Networks
Copyright policy )Slow Invariant Manifolds of Fast-Slow Systems of ODEs with Physics-Informed Neural Networks
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
physics-informed neural networks, slow invariant manifolds, machine learning, numerical methods, Numerical methods for ordinary differential equations, Multiple scale methods for ordinary differential equations, Invariant manifolds for ordinary differential equations, fast-slow dynamical systems, Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.), Artificial neural networks and deep learning
physics-informed neural networks, slow invariant manifolds, machine learning, numerical methods, Numerical methods for ordinary differential equations, Multiple scale methods for ordinary differential equations, Invariant manifolds for ordinary differential equations, fast-slow dynamical systems, Kinetics in biochemical problems (pharmacokinetics, enzyme kinetics, etc.), Artificial neural networks and deep learning
selected citations These citations are derived from selected sources.This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).0 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Average influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Average impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Average
Citations provided by BIP!Popularity provided by BIP!