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disentangled-representation-papers

A curated list of research papers related to learning disentangled representations

diva

Implementation of 'DIVA: Domain Invariant Variational Autoencoders'

ebm-defense

PyTorch implementation of BPDA+EOT attack to evaluate adversarial defense with an EBM

expcourse

Course materials for "Experimentation and Causal Inference"

fairface

FairFace: Face Attribute Dataset for Balanced Race, Gender, and Age

foolbox

A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX

ganhacks

starter from "How to Train a GAN?" at NIPS2016

gan_metrics-tensorflow

Simple Tensorflow implementation of metrics for GAN evaluation (Inception score, Frechet-Inception distance, Kernel-Inception distance)

gan_stability

Code for paper "Which Training Methods for GANs do actually Converge? (ICML 2018)"

gpytorch

A highly efficient and modular implementation of Gaussian Processes in PyTorch

iap-cidl

Causal Inference & Deep Learning, MIT IAP 2018

icip2019-image-translation-tutorial

imagenet-datasets-downloader

ImageNet dataset downloader. Creates a custom dataset by specifying the required number of classes and images in a class.

imgclsmob

Sandbox for training deep learning networks

inception-score-pytorch

Inception Score for GANs in Pytorch

interventions-disparate-impact-responders

Assessing Disparate Impacts of Personalized Interventions: Identifiability and Bounds

l-bfgs-based-adversarial-input-against-svm-

SVM,Machine Learning, Adversarial Attack

machine-learning-and-artificial-intelligence

Resources to learn more about Machine Learning and Artificial Intelligence

metrics

IS, FID score Pytorch and TF implementation, TF implementation is a wrapper of the official ones.

mister_ed

Pytorch Adversarial Attack Framework

mnist_challenge

A challenge to explore adversarial robustness of neural networks on MNIST.

multimodal-deep-learning-for-disaster-response

Damage Identification in Social Media Posts using Multimodal Deep Learning: code and dataset

odin-pytorch

Principled Detection of Out-of-Distribution Examples in Neural Networks

once-for-all-adversarial-training

[NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong Chen*, Shupeng Gui, Ting-Kuei Hu, Ji Liu, and Zhangyang Wang

papers-of-robust-ml

Related papers for robust machine learning

poli273

Course Website for Causal Inference at UCSD

pretrained-models.pytorch

Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.

provable-training-and-verification-approaches-towards-robust-neural-networks

This repo keeps track of popular provable training and verification approaches towards robust neural networks, including leaderboards on popular datasets and paper categorization.

pytorch-101-tutorial-series

PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

pytorch-adversarial-training

PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.