JiangNguyen's repositories

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altimeter_read

Read satellite altimetry data of Netcdf format

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Bayesian_NN_Ensembles

AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'

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Data_Assimilation

MSc Research project (6 months). Data Assimilation using Deep Learning (AEs). Imperial College Machine Learning MSc 2018-19

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discrete-continuous-bdl

Uncertainty Quantification of Disctete-Continuous Distribution with Bayesian Deep Learning in KDD 2018

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effect-of-climate-on--agriculture

This repository contains all the data set and coding used in the manuscript Rattis et al submitted to NCC

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FactSeg

FactSeg: Foreground Activation Driven Small Object Semantic Segmentation in Large-Scale Remote Sensing Imagery (TGRS)

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GSMaP

Python3 script of Reading GSMaP data.

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Landsat-Classification-Using-Convolution-Neural-Network

Source code and files mentioned in the medium post titled "Is CNN equally shiny on mid-resolution satellite data?" available at https://towardsdatascience.com/is-cnn-equally-shiny-on-mid-resolution-satellite-data-9e24e68f0c08

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Landsat-Classification-Using-Neural-Network

All the files mentioned in the article on Towards Data Science Neural Network for Landsat Classification Using Tensorflow in Python | A step-by-step guide.

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malawi-flood-prediction

TensorFlow implementation of a Multi-Input ConvLSTM for predicting flood extent.

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MARRMoT

Modular Assessment of Rainfall-Runoff Models Toolbox - Matlab code for 46 conceptual hydrologic models

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ml_flood

Machine learning to predict floods

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mosaiks-paper

Code and data to support our paper

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ParallelSWAT

Parallel computing-based and Spatially stepwise calibration of SWAT with streamflow observaitons and Satellite-based ET

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PM2.5-GNN

PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting

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PSTCR

Q. Zhang, Q. Yuan, J. Li, Z. Li, H. Shen, and L. Zhang, "Thick Cloud and Cloud Shadow Removal in Multitemporal Images using Progressively Spatio-Temporal Patch Group Learning", ISPRS Journal, 2020.

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RNN-RC-Chaos

RNN architectures trained with Backpropagation and Reservoir Computing (RC) methods for forecasting high-dimensional chaotic dynamical systems.

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SupReME

Super-Resolution of Multispectral Multiresolution Images from a Single Sensor

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tshydro

R package that estimates water level time series from satellite altimetry data

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ypea110-shuffled-complex-evolution

Shuffled Complex Evolution (SCE-UA) in MATLAB

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