John C. Teixeira's repositories
FracPaQ
Quantification of Fracture Patterns
IPARS_PhD
Code framework I worked on during my PhD at UT Austin
PyMVPA
MultiVariate Pattern Analysis in Python
pymc3
Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Theano
Generalized_Poroelastic_Model_FEniCS
The model code for the poroelastic model assocaited with the article title "A generalized poroelastic model using FEniCS with insights into the Noordbergum effect" by Haagenson et al. published in Computers & Geosciences.
PyDMD
Python Dynamic Mode Decomposition
bnpy
Bayesian nonparametric machine learning for Python
pyamg
Algebraic Multigrid Solvers in Python
uncertainpy
Uncertainpy: a Python toolbox for uncertainty quantification and sensitivity analysis, tailored towards computational neuroscience.
3rdParty-Stokes_LEoPart
A mirror of LEoPart from https://bitbucket.org/jakob_maljaars/leopart/src/master/
SOFTX_2018_73
FEniCS mechanics: A package for continuum mechanics simulations. To cite this software publication: https://www.sciencedirect.com/science/article/pii/S2352711018300979.
tutmom
Tutorial on "Modern Optimization Methods in Python"
AwesomeThermodynamics
A curated list of awesome resources on Thermodynamics
CO2-Sequestration
Carbon Capture and Sequestration (CCS) has been proposed as a promising and necessary technology for mitigating CO2 and the effects of anthropogenic climate change. Deep geological formations, like saline aquifers, are pointed out as promising areas for large-scale storage of CO2. If CCS is implemented on large scale to make noticeable reductions in atmospheric CO2, then it will require a solid scientific foundation defining the coupled hydrologic–geochemical–geomechanical processes that govern the long-term fate of CO2 in the subsurface, migration behavior of CO2, trapping mechanisms, proper utilization of methods to characterize and select sequestration sites, workflow and evaluation process, simulation methods, subsurface engineering to optimize performance, well placement, injection rate and cost, approaches to ensure safe operation, monitoring technology, remediation methods, regulatory overview, and an institutional approach for managing long-term liability. To address the above issues, we demonstrated, reviewed and developed the overall workflow of the process of CO2 sequestration in this study.
awesome-open-geoscience
Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
mit-deep-learning
Tutorials, assignments, and competitions for MIT Deep Learning related courses.
gempy
GemPy is an open-source, Python-based 3-D structural geological modeling software, which allows the implicit (i.e. automatic) creation of complex geological models from interface and orientation data. It also offers support for stochastic modeling to adress parameter and model uncertainties.
cheatsheets-ai
Essential Cheat Sheets for deep learning and machine learning researchers
chaospy
Chaospy - Toolbox for performing uncertainty quantification.
homemade-machine-learning
🤖 Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained
hybrid_HROM
FEniCS implementation of the hybrid reduced order/full‐order modeling strategy for nonlinear dynamic problems.
reaktoro
a unified framework for modeling chemically reactive systems
simulation_based_calibration
Implementation of simulation based calibration in PyMC3
deep-uq-paper
A repository that contains scripts to replicate results in the Deep UQ paper.
uq-course
Introduction to Uncertainty Quantification
Statistical-Inference-for-Everyone
Introductory Statistical Inference
hydrateflash
Thermodynamic stability calculation for mixed clathrate hydrates
pdfFoam
Transported JPDF Library and Solver for Reactive Flow Simulations with OpenFOAM