TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion
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Updated
Jul 3, 2026 - Python
TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion
launch missiles through atmosphere and space on a spherical spinning Earth to hit a specified target
Ordinary Differential Equation Framework, written in Pure Rust
Numerical resolution and stability analysis of a system of ordinary differential equations (ODEs) with high stiffness coefficient, using homogeneous, non-homogeneous and adaptive meshes. Implements Radau_IIA, Gauss-Legendre, BDF, Crank-Nicolson, Implicit Euler and Pareschi-Russo with LU factorization optimization.
C++ implementation of Euler, modified Euler, RK2, RK4, and Adams explicit methods for solving y'' = f(x, y, y') with adaptive step-size selection and L₁, L₂, L∞ error estimation.
Adaptive step size control for explicit Runge–Kutta ODE solvers in MATLAB, including BS3(2), ERK4(3), and DP5(4) methods.
MATLAB benchmark suite for comparing numerical integrators on classical differential-equation problems, including linear decay, harmonic oscillator, Van der Pol, Lorenz, Robertson kinetics, and Kepler two-body dynamics. The repository includes performance plots, accuracy metrics, conservation analysis, and a simulation video available on YouTube.
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