NUMERical methods for solving the AdvecTion Equation (NUMERATE)
-
Updated
Oct 11, 2023 - Python
NUMERical methods for solving the AdvecTion Equation (NUMERATE)
This repository contains Python code for numerical simulation, data analysis, and figures associated with the Herho et al. (2024) manuscript.
Simulations for a minimal model of the dynamics of wave propagation of the action potentials in human ventricular tissue. In 2016.
Code repository for the paper Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations
Finite element solver for partial differential equations on arbitrary meshes
Tercera tarea del curso Modelación y Computación Gráfica: Diferencias finitas. Visualización 3D de un acuario con zonas de temperatura dadas al resolver una EDP.
A selection of algorithms, implemented during the courses at UNI-LJ.
MSci thesis - modelling the development of neural connections in the visual system
A series of problems solved using finite difference methods, implemented in Python.
An easy-to-use, Python library designed to approximate solutions to partial differential equations using primarily, finite difference methods.
Modeling Heat Conduction with Two-Dissipative Variables: A Mechanism-Data Fusion Method
Python implementation of the classic Bubnov-Galerkin method for solving differential equations. Supports 1-3 dimensional problems.
Euler method for numerical integration of ordinary differential equations (ODEs). The Euler method is a simple and widely used numerical technique for solving initial value problems.
Modelling code for Illukkumbura et al., 2020
PyMiniWeather solves the compressible form of inviscid two-dimensional unsteady Euler equations using a finite volume discretization scheme and can run on multiple CPUs or GPUs without any code changes to the serial code using cuNumeric
PDE solvers in python for Cahn Hilliard and Boundary Value Problem simulations
A program designed to solve partial differential equations using neural networks, that uses Theano for symbolic computation.
Code for the paper ``Error Bounds for Learning with Vector-Valued Random Features''
Add a description, image, and links to the partial-differential-equations topic page so that developers can more easily learn about it.
To associate your repository with the partial-differential-equations topic, visit your repo's landing page and select "manage topics."