CIA-Oceanix/DINAE_keras

Stars
1
Language
Python
Created about 4 years ago
Updated over 3 years ago

CIA-Oceanix/DINAE_keras

CIA-Oceanix

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

End-to-end learning (see Fablet et al., 2019)

GeoTrackNet

A Maritime Anomaly Detector using Probabilistic Neural Network Representation of AIS Tracks and A Contrario Detection

TrAISformer

Pytorch implementation of TrAISformer---A generative transformer for AIS trajectory prediction (https://arxiv.org/abs/2109.03958).

4dvarnet-core

Core implementation of the 4DVarNet architecture

DLGD2022

Jupyter Notebook

DLOA2023

Introductory course on Deep Learning for Ocean and Atmosphere Dynamics

Jupyter Notebook

4dvarnet-starter

Streamlined version of the 4dvarnet algorithm: probably a good starting point to understand and applying it

Conditional_StyleGAN2_pytorch

DLGD2021

Jupyter Notebook

ai4oac2023

Jupyter Notebook

DAODEN

Implementation of Data-Assimilation-based ODE Network (DAODEN) (https://arxiv.org/abs/2009.02296)

Jupyter Notebook

DinAE_4DVarNN_torch

Jupyter Notebook

DetideNet

DetideNet: Filtering Internal tides from wide-swath altimeter data using Convolutional Neural Networks

Jupyter Notebook

DriftNet

A novel fully-convolutional architecture inspired from the Eulerian Fokker-Planck representation of Lagrangian dynamics at sea surface

Jupyter Notebook

CIA-Oceanix.github.io

NbedDyn

Learning latent dynamics for partially-observed chaotic systems

Jupyter Notebook

Dynamical_Systems_Identification

On the data-driven identification of some dynamical systems, linear regression, NODEs ...

Jupyter Notebook

Augmented_Koopman

Jupyter Notebook

MediSAR

Bounded-NbedDyn

Implementation of the Neural Embedding model with boundedness constraints

Jupyter Notebook

JeanZayTools

SAR-Segmentation

DLCourse_MOi_2022

Jupyter Notebook

4DVN-MM-W2D

Reconstruction of high-resolution wind speed fields from local and low-resolution wind speed fields