DataLearning

DA-tutorial-

introduction to DA

Digital-twin-LA-global-wildfire

gcn-lstm-wildfire

LatentAssimilation

LatentGAN

ML_surrogate_model_wildfires

ML surrogate model which combines ROM, LSTM and DA for dynamical systems such as wildfires

mspcnn-for-dynamic-system

ROMS-tutorial

SCDNN-TS

VIVID

DL-WG/gcn-lstm-wildfire

DL-WG/mspcnn-for-dynamic-system

DL-WG/SCDNN-TS

DL-WG/DA-tutorial-

introduction to DA

DL-WG/Digital-twin-LA-global-wildfire

DL-WG/VIVID

DL-WG/ViTAE

ViTAE: a vision transformer-based autoencoder and spatial interpolation learner for field reconstruction

DL-WG/Acoustic_emission_-_ML

DL-WG/Breathe-in-Breathe-out

DL-WG/DA_material

DL-WG/DL_Surrogate_JULES_INFERNO

DL-WG/drop-coalescence-surrogate-model-and-LA

DL-WG/dscvae-for-drop-coalescence

DL-WG/Explainable-AI-for-Drop-Coalescence

DL-WG/FIDN

Fire-Image-DenseNet - A model for predicting the final burnt area of wildfire

DL-WG/GLA_with_ROSM

In this project, we introduce the Generalised Latent Assimilation (GLA) approach which can be used in Machine learning surrogate modelling for dynamical systems

DL-WG/MEDLA-Multi-domain-encoder-decoder-neural-networks-for-latent-data-assimilation-in-dynamical-systems

DL-WG/DataLearningParadigm

Code repository for the data learning paper

DL-WG/AirQualityDisease

DL-WG/CMCC

DL-WG/datalearning-seminars

DL-WG/datalearning-seminars.github.io

DL-WG/diameter_inverse

DL-WG/Digital_twin_LA_global_wildfire

DL-WG/HPC-training

Python and bash script for training on HPC

DL-WG/Nuclear_reactor_VCNN

This repository includes the code for fast field reconstruction using Voronoi tessellation and CNN techniques

DL-WG/premiereDroplets

DL-WG/SCDNN_TS

DL-WG/Surrogate_model_JULES_INFERNO

DL-WG/WaveSuite

Generative networks for expand the design space of point absorber Wave Energy Converters (WECs)