Workshop materials for training in scientific computing and scientific machine learning
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Updated
May 6, 2024 - Julia
Workshop materials for training in scientific computing and scientific machine learning
Rust low level bindings to the Sundials library
Library for multistep and multistage integration of ODEs
Numerical Methods
Introduction to analyze piecewise-smooth systems using python
Learning the basics of epidemic modelling via compartmental models in Python
Part of MSc Biology Project (2/2). Ordinary Differential Equations (ODE) model for modelling protein, more specifically Sfp1, translocation.
A fast and flexible C++ simulation engine and differential equation solver.
The folder contains implemented approaches of curves fitting of Non-Specific binding of Blood Plasma proteins to the sensor surface
Lorenz system - Repository for the project for Software and Computing for Applied Physics
Mechanistic models in fermentation
Particle flow animation with the trajectories of the particles being computed using the function odeint from scipy.integrate.
Ordinary Diferential Equations
Modeling and simulation of LTI state-space and nonlinear systems.
Methods for solving systems of ordinary differential equations in the case of initial value problems (ODE-IVP).
Solving initial value problems in pharmacometric modeling using TensorFlow
Numerically solving the dynamical equations of a protein expression system
This is a program that provides a graphical solution for the population inversion of the levels 2 and 3 of the Argon laser atomic system.
Collection of C++ codes for the computation of Bruggeman effective medium refractive index spectra.
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