Imagen de Portada

Correcting Auto-Differentiation in Neural-ODE Training

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Xu, Yewei, Chen, Shi, Li, Qin
Formato:	Preprint
Publicado:	2023
Materias:	Machine Learning Numerical Analysis 65D25 (Primary), 65L06, 90C31 (Secondary)
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A novel interpretation of Nesterov's acceleration via variable step-size linear multistep methods
por: Nozawa, Ryota, et al.
Publicado: (2024)

Sensitivity analysis of an epidemic model with a mass vaccination program of a homogeneous population
por: Bargo, Ma. Cristina R.
Publicado: (2025)

Spectral Deferred Corrections in the framework of Runge-Kutta methods
por: Bronasco, Eugen, et al.
Publicado: (2026)

A C++ implementation of the discrete adjoint sensitivity analysis method for explicit adaptive Runge-Kutta methods enabled by automatic adjoint differentiation and SIMD vectorization
por: Martins, Rui, et al.
Publicado: (2024)

A Priori Estimates for the Global Error Committed by Runge-Kutta Methods for a Nonlinear Oscillator
por: Niesen, Jitse
Publicado: (2001)

On the connections between optimization algorithms, Lyapunov functions, and differential equations: theory and insights
por: Dobson, Paul, et al.
Publicado: (2023)

Derivatives of the full QR factorisation and of the factored-form and compact WY representations
por: Papanicolopulos, Stefanos-Aldo
Publicado: (2024)

Multi-Order Runge-Kutta Methods or how to numerically solve initial value problems of any order
por: Petronijevic, Loris
Publicado: (2025)

Runge-Kutta methods, trees, and Mathematica
por: Bornemann, Folkmar
Publicado: (2002)

Error estimates of fully semi-Lagrangian schemes for diffusive conservation laws
por: Takemura, Haruki
Publicado: (2025)

Error estimates for semi-Lagrangian schemes with higher-order interpolation for conservation laws with dispersive terms
por: Takemura, Haruki
Publicado: (2025)

Revisiting Sparse Matrix Coloring and Bicoloring
por: Montoison, Alexis, et al.
Publicado: (2025)

Accelerating the Simulation of Ordinary Differential Equations Through Physics-Preserving Neural Networks
por: Tagg, Andrew, et al.
Publicado: (2026)

Differentiable Programming for Differential Equations: A Review
por: Sapienza, Facundo, et al.
Publicado: (2024)

Extending Data to Improve Stability and Error Estimates Using Asymmetric Kansa-like Methods to Solve PDEs
por: Hangelbroek, Thomas, et al.
Publicado: (2025)

Randomized subspace correction methods for convex optimization
por: Jiang, Boou, et al.
Publicado: (2025)

Solving PDEs on Surfaces of Pipe Geometries Using New Coordinate Transformations and High-order Compact Finite Differences
por: Hu, Shuaifei, et al.
Publicado: (2025)

Modified Patankar Linear Multistep methods for production-destruction systems
por: Izzo, Giuseppe, et al.
Publicado: (2024)

Adaptive Multiquadratic Radial Basis Function-based Explicit Runge--Kutta Methods
por: Yadav, Rajesh, et al.
Publicado: (2025)

The Global R-linear Convergence of Nesterov's Accelerated Gradient Method with Unknown Strongly Convex Parameter
por: Bao, Chenglong, et al.
Publicado: (2023)

Accelerated Gradient Methods with Gradient Restart: Global Linear Convergence
por: Bao, Chenglong, et al.
Publicado: (2024)

On the unconventional Hug integrator
por: Andrieu, Christophe, et al.
Publicado: (2025)

Efficient Numerical Evaluation of Triple Integral Using the Euler's Method and Richardson's Extrapolation
por: Gupta, Shubhangini, et al.
Publicado: (2025)

An insight on some properties of high order nonstandard linear multistep methods
por: Takács, Bálint
Publicado: (2025)

Accelerated optimization algorithms and ordinary differential equations: the convex non Euclidean case
por: Dobson, Paul, et al.
Publicado: (2024)

Consistency of Learned Sparse Grid Quadrature Rules using NeuralODEs
por: Gottschalk, Hanno, et al.
Publicado: (2025)

High Order semi-implicit Rosenbrock type and Multistep methods for evolutionary partial differential equations with higher order derivatives
por: Sebastiano, Boscarino, et al.
Publicado: (2026)

Derivative-free discrete gradient methods
por: Myhr, Håkon Noren, et al.
Publicado: (2026)

A Convergent Numerical Algorithm for $α$-Dissipative Solutions of the Hunter-Saxton Equation
por: Christiansen, Thomas, et al.
Publicado: (2023)

A numerical view on α-dissipative solutions of the Hunter-Saxton equation
por: Christiansen, Thomas, et al.
Publicado: (2024)

Kahan's Automatic Step-Size Control for Unconstrained Optimization
por: Meng, Yifeng, et al.
Publicado: (2025)

An additive two-level parallel variant of the DMRG algorithm with coarse-space correction
por: Grigori, Laura, et al.
Publicado: (2025)

A non-iterative domain decomposition time integrator combined with discontinuous Galerkin space discretizations for acoustic wave equations
por: Buchholz, Tim, et al.
Publicado: (2025)

Minimal Convex Environmental Contours
por: Sande, Åsmund Hausken, et al.
Publicado: (2023)

On Trigonometric Interpolation and Its Applications
por: Zou, Xiaorong
Publicado: (2025)

Sample-based almost-sure quasi-optimal approximation in reproducing kernel Hilbert spaces
por: Hegemann, Nando, et al.
Publicado: (2024)

A general framework for floating point error analysis of simplex derivatives
por: Chen, Yiwen, et al.
Publicado: (2024)

B-stability of numerical integrators on Riemannian manifolds
por: Arnold, Martin, et al.
Publicado: (2023)

Hierarchical Coarse Basis by Randomised SVD: the Helmholtz Problem
por: Gander, Martin J., et al.
Publicado: (2025)

Convergence and stability of randomized implicit two-stage Runge-Kutta schemes
por: Bochacik, Tomasz, et al.
Publicado: (2024)