JiangNguyen's repositories
AtmDS
This repository is under construction. It will be used to store all necessary function for the downscaling of atmspheric forcing variables.
bayesian-hydrological-modeling
Mini Project on Bayesian treatment of hydrological models
Bayesian_optimization_deep_learning
optimized parameters of deep learning using Bayesian optimization
Bayesian_uncertainty_LSTM
Bayesian, Uncertainty, Neutral Networks, LSTM, time series
bayesian_unet
Chainer implementation of Bayesian Convolutional Neural Networks (BCNNs)
cnn-surrogate
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
dcstfn
Deep Convolutional SpatioTemporal Fusion Network (DCSTFN)
DSen2_Implementation
A operational implementation of the DSen2 Model
EEwPython
A series of Jupyter notebook to learn Google Earth Engine with Python
ggplot2_dataviz
Codes from "Professional dataviz with ggplot2" video series from my YouTube channel.
GraphNeuralNet
A simple Graph Net in PyTorch
GWR-OI
A two-step merging and downscaling method for satellite precipitation
incertae
Code for MC Dropout and Model Ensembling Uncertainty Estimate experiments
meteoai
The papers or tutorials and relative source code of artificial intelligence for meteorology, ocean and environment science.
MFCTR-CNN
Tensorfolw code for" Reconstructing Geostationary Satellite Land Surface Temperature Imagery Based on Multiscale Feature Connected Convolutional Neural Network"(Remote sensing 2019)
Mojtaba-Sadeghi
environmental modelling & software journal
NAM_Model
Python implementation of NedborAfstromnings Model (NAM) lumped rainfall–runoff model
nexrad_sr
Code for: "Radar Super Resolution using a Deep Convolutional Neural Network" by Andrew Geiss and Joseph C. Hardin
PanNet-Landsat
Implementation of "PanNet: A deep network architecture for pan-sharpening"
Papers-on-Spatial-Temporal-Graph-Neural-Networks
Papers on Spatial-Temporal Graph Neural Networks
Parametric_UQ_BS_option_pricing
This repository includes Matlab codes/routines that were used in my Bachelor thesis entitled "Numerical Methods For Uncertainty Quantification In Option Pricing" that can be found in: https://www.researchgate.net/publication/330005261_Numerical_Methods_For_Uncertainty_Quantification_In_Option_Pricing.
pde-surrogate
Physics-constrained deep learning for high-dimensional surrogate modeling and uncertainty quantification without labeled data
PINNs
Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations
Polynomial-Chaos-Expansion-Examples
Recreate plots in Paper 'THE WIENER–ASKEY POLYNOMIAL CHAOS FOR STOCHASTIC DIFFERENTIAL EQUATIONS'
pytorch_bayesian_unet
Migrate to PyTorch. Re-implementation of Bayesian Convolutional Neural Networks (BCNNs)
Rain_Processors
This repository contains Matlab codes I made to process different satellite precipitation products.
validation_good_practice
Source code for the soil moisture validation good practice paper