Results 21 to 30 of about 36,652 (259)
Computability of Ordinary Differential Equations [PDF]
, 2018 In this paper we provide a brief review of several results about the computability of initial-value problems (IVPs) defined with ordinary differential equations (ODEs). We will consider a variety of settings and analyze how the computability of the IVP will be affected.
Graça, Daniel, Zhong, Ning
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Optical neural ordinary differential equations
Optics Letters, 2023 Increasing the layer number of on-chip photonic neural networks (PNNs) is essential to improve its model performance. However, the successive cascading of network hidden layers results in larger integrated photonic chip areas. To address this issue, we propose the optical neural ordinary differential equations (ON-ODEs) architecture that parameterizes ...
Yun Zhao +7 more
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Advances in Mechanical Engineering, 2016 A simplified variational iteration method is proposed to solve high-order homogeneous or nonhomogeneous linear ordinary differential equation and ordinary differential equation eigenvalue problems more efficiently and conveniently.
Chao Pan, Ruifu Zhang, Hao Luo, Hua Shen
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Mathematics, 2021 This paper studies a non-linear viscoelastic wave equation, with non-linear damping and source terms, from the point of view of the Lie groups theory.
Almudena P. Márquez, María S. Bruzón
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Predicting Ordinary Differential Equations with Transformers
CoRR, 2023 We develop a transformer-based sequence-to-sequence model that recovers scalar ordinary differential equations (ODEs) in symbolic form from irregularly sampled and noisy observations of a single solution trajectory. We demonstrate in extensive empirical evaluations that our model performs better or on par with existing methods in terms of accurate ...
Becker, S. +4 more
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SOLUSI DARI PERSAMAAN CAUCHY–EULER NONHOMOGEN KASUS LOGARITMIK
E-Jurnal Matematika, 2020 Ordinary differential equation is one form of differential equations that are often found in everyday life. One form of ordinary differential equations which has non–constant coefficients is the Cauchy–Euler differential equation.
I GEDE PUTU MIKI SUKADANA +2 more
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Solving the Generalized Rosenau-KdV Equation by the Meshless Kernel-Based Method of Lines
Cumhuriyet Science Journal, 2022 This current investigation consists of the numerical solutions of the Generalized Rosenau-KdV equation by using the meshless kernel-based method of lines, which is a truly meshless method.
Murat Arı +2 more
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Neural Ordinary Differential Equations
CoRR, 2018 We introduce a new family of deep neural network models. Instead of specifying a discrete sequence of hidden layers, we parameterize the derivative of the hidden state using a neural network. The output of the network is computed using a black-box differential equation solver.
Tian Qi Chen +3 more
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Solving Ordinary Differential Equations with Discontinuities [PDF]
ACM Transactions on Mathematical Software, 1984 Automatic codes for differential equations can be inadequate when the solutions have discontinuities. If the user provides an external indicator for discontinuities (e.g., a switching function whose sign changes indicate discontinuities), a code can be more efficient.
Gear, C. W., Østerby, Ole
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Characteristic Neural Ordinary Differential Equations
CoRR, 2021 We propose Characteristic-Neural Ordinary Differential Equations (C-NODEs), a framework for extending Neural Ordinary Differential Equations (NODEs) beyond ODEs. While NODEs model the evolution of a latent variables as the solution to an ODE, C-NODE models the evolution of the latent variables as the solution of a family of first-order quasi-linear ...
Xingzi Xu +4 more
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