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2d-cnn-denoise-unet

adcme.jl

Automatic Differentiation Library for Computational and Mathematical Engineering

adseismic.jl

A General Approach to Seismic Inversion Problems using Automatic Differentiation

adversarial_video_generation

A TensorFlow Implementation of "Deep Multi-Scale Video Prediction Beyond Mean Square Error" by Mathieu, Couprie & LeCun.

ajmalkoti.github.io

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

birdsong-generation-project

Generating birdsong with WaveNet

cdncnn-b-tensorflow

CDnCNN-B for blind color image denoising - Tensorflow implementation

cnn

CNN with and without batch normalization

cnn-for-asi

Tutorial: Convolutional Neural Networks for Automated Seismic Interpretation

cnn-fwi

cnn-image-denoising

Image Denoising with Convolutional Neural Networks

cnn_image_denoising

code:《基于深度卷积神经网络的图像去噪研究》

compression

Data compression in TensorFlow

constant-q-pstd

convnetdraw

Draw multi-layer neural network in your browser

datasets

A collection of datasets ready to use with TensorFlow

deepwave

Wave propagation modules for PyTorch.

deepxde

A library for scientific machine learning and physics-informed learning

denoising-cnn

dncnn-denoise-gaussian-noise-tensorflow

Simple implementation of the paper (DnCNN)'Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising'

dncnn-tensorflow

:octocat::octocat:A tensorflow implement of the paper "Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising"

edge-based-dictionary-learning

edge based dictionary learning for image denoising

fast-style-transfer

TensorFlow CNN for fast style transfer ⚡🖥🎨🖼

fast-wavenet

Speedy Wavenet generation using dynamic programming :zap:

fastfwi

Simple frequency domain full-waveform inversion (FWI) regularized by Sobolev space norm

fftw3

DO NOT CHECK OUT THESE FILES FROM GITHUB UNLESS YOU KNOW WHAT YOU ARE DOING. (See below.)

fid-cnn

The source code of <A Fractional Total Variational CNN Approach for SAR Image Despeckling>

fwi-using-temporal-fourth-fd-modelling-1

These codes are used to complete elastic full waveform inversion using temporal fourth-order FD modelling. In order to accelete the algorith, GPU-based versions are privided here. What's more, the GPU shared memory is used in block level and the efficiency improvement is about 10%~15% on GTX 750ti, where efficiency improvement is dependent on the length of FD orders.

fwigan

FWIGAN: Full-Waveform Inversion with Deep Adversarial Learning