A neural network maps ODE states to a slow-evolving latent space with dynamics derived from the original equations via the chain rule, enabling accelerated simulations with fewer function calls.
Algorithms and numerical methods for high dimensional financial market models.Revista de Economia Financiera, 20:51–68, 2010
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Accelerating the Simulation of Ordinary Differential Equations Through Physics-Preserving Neural Networks
A neural network maps ODE states to a slow-evolving latent space with dynamics derived from the original equations via the chain rule, enabling accelerated simulations with fewer function calls.