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a-pytorch-tutorial-to-machine-translation

Attention Is All You Need | a PyTorch Tutorial to Machine Translation

adversarial-example

Crafting Adversarial Examples with PyTorch

adversarial-examples-in-pytorch

Pytorch code to generate adversarial examples on mnist and ImageNet data.

adversarial-examples-paper

Paper list of Adversarial Examples

adversarial-examples-reading-list

This is the reading list mainly on adversarial examples (attacks, defenses, etc.) I try to keep and update regularly.

adversarial-mnist

generating adversarial examples to fool a MNIST classifier

advgan_pytorch

a Pytorch implementation of the paper "Generating Adversarial Examples with Adversarial Networks" (advGAN).

age-estimation-pytorch

PyTorch-based CNN implementation for estimating age from face images

ares121

A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

audio_adversarial_examples

Targeted Adversarial Examples on Speech-to-Text systems

awesome-graph-attack-papers

Adversarial attacks and defenses on Graph Neural Networks.

awesome-pytorch-list

A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

code

crowd-counting

Awesome Crowd Counting

crowd_couting_live_can

Real-Time Crowd Counting Using CANNet

cw_linf

Pytorch Reimplementation of Carnili-Wagner Attack.

deeprobust

A pytorch adversarial library for attack and defense methods on images and graphs

dense_adversarial_generation_pytorch

di-2-fgsm

Improving Transferability of Adversarial Examples with Input Diversity

examples

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.

fbpca

Fast Randomized PCA/SVD

fgsm

Simple pytorch implementation of FGSM and I-FGSM

format

ACM consolidated LaTeX styles

gans

Generative Adversarial Networks implemented in PyTorch and Tensorflow

generating-images-from-noise-using-gans

generative-adversarial-networks-for-computer-vision

Deep Neural Networks to build a generator that generates new images from noise and a discriminator function for identifying the true images from the fake images

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

image-perturbation-defense

Research Thesis on defending against adversarial attack in Deep Learning