Grid-based approximation of partial differential equations in Julia
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Updated
Sep 20, 2024 - Julia
Grid-based approximation of partial differential equations in Julia
Geophysical fluid dynamics pseudospectral solvers with Julia and FourierFlows.jl.
Finite-element toolbox in Julia
Python package for solving partial differential equations using finite differences.
Solver for 1D nonlinear partial differential equations in Julia based on the collocation method of Skeel and Berzins and providing an API similar to MATLAB's pdepe
Rensselaer's Optimistic Simulation System
Deep learning approaches to PDEs
Generative Pre-Trained Physics-Informed Neural Networks Implementation
Spatial bio-chemical reaction model editor and simulator
NRPy+, BlackHoles@Home, SENRv2, and the NRPy+ Jupyter Tutorial: Python-Based Code Generation for Numerical Relativity... and Beyond!
This repository contains my thesis work on the control of RBC using symmetry exploiting deep reinforcement learning
Code for the paper "Poseidon: Efficient Foundation Models for PDEs"
pseudospectral (fourier) solutions of a few 1-dimensional PDEs
Modelling the phenomenon of "Ecological Suicide", for a final year Master's project in Engineering Mathematics.
This repository contains code and documentation for solving the cardiac electrophysiology problem using Finite Element methods. It includes implementations in deal.II, mesh generation with gmsh, and visualization using ParaView.
Three Dimensional Magnetohydrodynamic(MHD) pseudospectral solvers written in julia with FourierFlows.jl
Julia code to fit mechanistic-statistical models w/ Bayes and MCMC
A Stochastic Primal-Dual Proximal Splitting Method for Risk-Averse Optimal Control of PDEs
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