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daveb-dev's Projects

sttp icon sttp

Spectral Tensor Train Parameterization of Deep Learning Layers

tardigrade icon tardigrade

Repository for creating a new MOOSE based application

taurus icon taurus

taurus library for model order reduction

tetridiv icon tetridiv

Python package to subdivide tetrahedral meshes in hexahedral meshes, and triangular meshes into quadrilateral meshes.

tfel icon tfel

Public clone of the svn repository of TFEL/MFront

tigar icon tigar

A Python library for isogeometric analysis (IGA) using FEniCS.

tinyekf icon tinyekf

Lightweight C/C++ Extended Kalman Filter with Python for prototyping

tlm_adjoint icon tlm_adjoint

A library for high-level algorithmic differentiation, principally for models written using FEniCS or Firedrake.

toot_gt icon toot_gt

Topology optimization using optimal transport distances

trilinos icon trilinos

Live clone of Trilinos's Git repository (https://software.sandia.gov/trilinos/repositories/publicTrilinos)

tutorials icon tutorials

Tutorials for the usage of the Uni.lu HPC platform

ufno icon ufno

U-FNO - an enhanced Fourier neural operator-based deep-learning model for multiphase flow

ula-statfem icon ula-statfem

Code to run statistical finite element method (statFEM) experiments with Langevin dynamics.

vtkplotter icon vtkplotter

A python class for scientific visualization of 3D objects with VTK

wmluncertaintyanalysis icon wmluncertaintyanalysis

This repository contains the scripts and code that is required to perform a tDCS uncertainity analysis. Further information will be detailed in the paper "The influence of white matter lesions on the electrical field in transcranial electric stimulation".

woo icon woo

Extensible and portable framework primarily for mechanics granular materials. Computation parts are written in c++ parallelized using OpenMP, fully accessible and modifiable from python (ipython console or scripts). Arbitrarily complex scene can be scripted. Qt-based user interface is provided, featuring flexible OpenGL display, inspection of all objects and runtime modification. Parametric preprocessors can be written in pure python, and batch system can be used to drive parametric studies. New material models and particle shapes can be added (in c++) without modifying existing classes.

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