Pinned Repositories
data_knowledge_driven_trend_surface
Stochastic geological surface modeling
FrEIA
Framework for Easily Invertible Architectures
gaussian-random-fields
Generator of 2D gaussian random fields
GEOL6396-Computational-EM
This repository contains Python codes for implementing 1D MT modeling, 3D DC modeling, 1D inversion and 3D sensitivity calculation. Created for the course - GEOL 6396 Computational EM in the Department of Earth and Atmospheric Sciences, University of Houston.
geosci-labs
collection of notebook-apps for concepts in applied geophysics
handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
SeisTomo_Tutorials
Seismic Body-wave Traveltime Tomography Tutorials
UHElectromagnetics
Jupyer Notebooks on EM modeling that helps students understant the physics involved in various EM surveys
UHMachineLearning
a collection of Jupyter Notebooks that implements machine learning algorithms.
UHPotentialFields
jiajiasun's Repositories
jiajiasun/UHElectromagnetics
Jupyer Notebooks on EM modeling that helps students understant the physics involved in various EM surveys
jiajiasun/UHMachineLearning
a collection of Jupyter Notebooks that implements machine learning algorithms.
jiajiasun/UHPotentialFields
jiajiasun/SeisTomo_Tutorials
Seismic Body-wave Traveltime Tomography Tutorials
jiajiasun/data_knowledge_driven_trend_surface
Stochastic geological surface modeling
jiajiasun/FrEIA
Framework for Easily Invertible Architectures
jiajiasun/gaussian-random-fields
Generator of 2D gaussian random fields
jiajiasun/GEOL6396-Computational-EM
This repository contains Python codes for implementing 1D MT modeling, 3D DC modeling, 1D inversion and 3D sensitivity calculation. Created for the course - GEOL 6396 Computational EM in the Department of Earth and Atmospheric Sciences, University of Houston.
jiajiasun/geosci-labs
collection of notebook-apps for concepts in applied geophysics
jiajiasun/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
jiajiasun/iris-mt-course-2022
jiajiasun/jiajiasun
Config files for my GitHub profile.
jiajiasun/normalizing-flows
PyTorch implementation of normalizing flow models
jiajiasun/pynoddy
pynoddy is a python package to write, change, and analyse kinematic geological modelling simulations performed with Noddy.
jiajiasun/Python-for-Earth-Science-Students
jiajiasun/python-geospatial
A collection of Python packages for geospatial analysis with binder-ready notebook examples
jiajiasun/pytorch-CycleGAN-and-pix2pix
Image-to-Image Translation in PyTorch
jiajiasun/segmentation_models.pytorch
Segmentation models with pretrained backbones. PyTorch.
jiajiasun/Seismology
Teaching material for ErSE 210 Seismology course
jiajiasun/simpeg
Simulation and Parameter Estimation in Geophysics - A python package for simulation and gradient based parameter estimation in the context of geophysical applications.