Chaoshun's repositories
Bayesian_Seismic_Inversion
The class computes the Bayesian Seismic Inversion results . Some modules are missing due to its proprietary natures, updates with an executable file is coming soon.
VTI_rays
VTI raytracing
Deep-Learning-in-Production
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
TOMO2D_2_TOY2DAC
A collection of Python algoritms to format seismic data for traveltime tomography in TOMO2D and full-waveform inversion in TOY2DAC
deep-nn-car
This is the repository for the DeepNNCar
RLexample-1
Some basic examples of playing with RL
EfficientNeuralArchitectureSearch
CS394R Final Project : Searching Efficient Neural Architectures using Reinforcement Learning
Machine_Learning_Tutorials
Code, exercises and tutorials of my personal blog ! 📝
RL_proj
Final project of course cs394R: Reinforcement Learning.
Basics
scripts to demonstrate concepts in signal/image processing, seismic modeling
CKAD-exercises
A set of exercises to prepare for Certified Kubernetes Application Developer exam by Cloud Native Computing Foundation
resnet1d
A PyTorch implementation of ResNet/ResNeXt with 1D conv (pad same), and its application on ECG data
seismic-data-regularization
A partial convolution-based deep-learning network for seismic data regularization
GAN_interp
Seismic data interpolation via WGAN
autoweb
Final project in CS394R: Reinforcement Learning Theory and Practice at UT Austin
4D-seismic-neural-inversion
Deep Neural Networks for Map-Based 4D Seismic Pressure-Saturation Inversion
CS394R_Final_Project
CS394R_Final_Project
dqn-transfer
UT Austin CS394R Reinforcement Learning course project
RL_Final_Project_2019
This is the course project for CS394R @ UT Austin
cs394-rl_project
Final project for CS394R: Implementation for D4PG Algorithm.
CS394R_Final_Project-1
Splitting PPO
RL-Project
CS394R Reinforcement Learning Project
reservoir_datasets
Various reservoir datasets, including Volve and PUNQS3
rloss
Regularized Losses (rloss) for Weakly-supervised CNN Segmentation
Reinforcement-Learning-Maze
Various ways to learn a computer to escape from a maze. From random walk to a simple neural network.
ckad-crash-course
In-depth and hands-on practice for acing the exam.
teslausb
Steps and scripts for turning a Raspberry Pi into a useful USB drive for a Tesla
NTU-ReinforcementLearning-Notes
国立**大学李宏毅老师讲解的深度强化学习学习笔记