Jean Ragusa's repositories
cbe67701-uncertainty-quantification
Summer 2020 reading group on uncertainty quantification
math_deep_learning_summer_school19
This repository contains material of the BMS Summer School Mathematics of Deep Learning
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
book
book
CompAI
Shot course on computational methods for AI
covid-19-analysis
Some simple example notebooks of public COVID-19 data analysis
DMD-for-ergodic-systems
Computing the discrete spectrum of the Koopman operator using Dynamic Mode Decomposition
FEconv
Program feconv is an utility to convert between several mesh and FE field formats, like ANSYS mesh files (.msh), MD Nastran input files (.bdf), I-Deas Universal (.unv), VTK files (.vtk), etc. If you use a Modulef format to store an intermediate mesh (.mfm). It can transform the FE type of a mesh composed of trangles or tetrahedra, to Lagrange P1 or P2, Raviart-Thomas (face) or Whitney (edge) finite elements. It also uses third-party code to perform bandwidth optimization (CutlHill-McKee optimization).
GPTutorial-1
A hands-on tutorial on supervised learning with Gaussian processes
intro-to-pytest
An introduction to PyTest with lots of simple, hackable examples
modred
Modred main repository
NumericalGP
Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
PINNs
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
PINNs-TF2.0
TensorFlow 2.0 implementation of Maziar Raissi's Physics Informed Neural Networks (PINNs).
SA-PINNs
Implementation of the paper "Self-Adaptive Physics-Informed Neural Networks using a Soft Attention Mechanism"
scientific-python-lectures
Lectures on scientific computing with python, as IPython notebooks.
shallow-water-eric
This is Dr. Jean-Luc Guermond's shallow water code, I will update later with instructions on how to set up, use, etc
slowpoke
A simple python tool for performing ultrafine-group neutron slowing down calculations
tugger-routing
Case-Study on Reinforcement Learning for Assembly Line Material Supply
uq-course
Introduction to Uncertainty Quantification
UQPINNs-TF2.0
TensorFlow 2.0 implementation of Yibo Yang, Paris Perdikaris’s adversarial Uncertainty Quantification in Physics Informed Neural Networks (UQPINNs).