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Found 6 papers, 1 papers with code
Structure-Preserving Physics-Informed Neural Networks With Energy or Lyapunov Structure
Experimental results demonstrate that the proposed method improves the numerical accuracy of PINNs for partial differential equations.
A modified model for topic detection from a corpus and a new metric evaluating the understandability of topics
This paper presents a modified neural model for topic detection from a corpus and proposes a new metric to evaluate the detected topics.
Lyapunov-Stable Deep Equilibrium Models
Deep equilibrium (DEQ) models have emerged as a promising class of implicit layer models, which abandon traditional depth by solving for the fixed points of a single nonlinear layer.
Composing a surrogate observation operator for sequential data assimilation
In data assimilation, state estimation is not straightforward when the observation operator is unknown.
Symplectic Adjoint Method for Exact Gradient of Neural ODE with Minimal Memory
The symplectic adjoint method obtains the exact gradient (up to rounding error) with memory proportional to the number of uses plus the network size.
Algorithms for the computation of the matrix logarithm based on the double exponential formula
In order to utilize the double exponential formula, we must determine a suitable finite integration interval, which provides the required accuracy and efficiency.
Numerical Analysis Numerical Analysis
