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adnet

Pytorch implementation of ADNet. (The winning method of the first edition of NTIRE2021 Multi-Frame HDR Challenge)

attention-module

Official PyTorch code for "BAM: Bottleneck Attention Module (BMVC2018)" and "CBAM: Convolutional Block Attention Module (ECCV2018)"

awesome-diffusion-models

A collection of resources and papers on Diffusion Models

beta-tcvae

code for "Isolating Sources of Disentanglement in Variational Autoencoders".

boundary-loss

Official code for "Boundary loss for highly unbalanced segmentation", runner-up for best paper award at MIDL 2019. Extended version in MedIA, volume 67, January 2021.

coursera-deep-learning-specialization

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-learning-specialization-coursera

Deep Learning Specialization courses by Andrew Ng, deeplearning.ai

deepdenoiser

DeepDenoiser: Seismic Signal Denoising and Decomposition Using Deep Neural Networks

deepkoopman

neural networks to learn Koopman eigenfunctions

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

deeponet

Learning nonlinear operators via DeepONet

deformable-convolution-v2-pytorch

Deformable ConvNets V2 (DCNv2) in PyTorch

deformable_convnet_pytorch

Pytorch implementation of Deformable Convolutional Network

devito

DSL and compiler framework for automated finite-differences and stencil computation

devito_book

Work in progress - Objective is to develop a comprehensive textbook on finite difference computing with Devito

dfno

Distributed Fourier Neural Operators

domain-adversarial-training-of-neural-networks

implement Domain-Adversarial Training of Neural Networks

esys-escript.github.io

fcnvmb-deep-learning-based-seismic-velocity-model-building

Deep-learning inversion: A next-generation seismic velocity model building method

fourier_neural_operator

Use Fourier transform to learn operators in differential equations.

fwigan

FWIGAN: Full-Waveform Inversion with Deep Adversarial Learning

geoml

Spatial modeling using machine learning concepts

gimli

Geophysical Inversion and Modeling Library :earth_africa:

glow-pytorch

PyTorch implementation of Glow

graph-neural-pde

Graph Neural PDEs

gravformodeling3d

code related to the paper "Forward modeling of gravity anomalies based on cell mergence and parallel computing"

image_segmentation

Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.

inn-surrogate

Solving inverse problems using conditional invertible neural networks.

invertiblenetworks.jl

A Julia framework for invertible neural networks