Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
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Updated
Jun 20, 2024 - Python
Solve forward and inverse problems related to partial differential equations using finite basis physics-informed neural networks (FBPINNs)
Code for training and inferring acoustic wave propagation in 3D
bzCompute is a computation graph library with built-in support for domain-decomposition and prallel computation. The library can be used for expressing and executing large number of mathematical and text-processing operations using Data-Flow graphs, (Educational version of tensorflow), written in pure python code with numpy support.
Python Library for rectangular decomposition of 2D binary images. Useful for ARD(Adaptive Rectangular Decomposition) sound simulation. 🐍 📦
Finite and boundary element methods on Python
Domain decomposition learning algorithms for elliptic boundary value problems, with focus on the classical Dirichlet-Neumann and Robin-Robin algorithms.
Vanishing Viscosity solution predicting Graph Neural Networks and Domain Decomposable Reduced Order Models based on the Discontinuous Galerking method applied to Friedrichs' systems
MSc project - Applied Computational Science and Engineering at Imperial College London 2021. Topic: Domain Decomposition and Generative Adversarial Networks (DD-GAN) for modelling fluid flow
The goal of this trial is to use the socket programming concept to connect cores belonging to the same processor and participate in solving a mathematical problem.
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