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Xiao Wang's Projects

l_dmi icon l_dmi

Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"

mae-1 icon mae-1

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

mean-teacher icon mean-teacher

A state-of-the-art semi-supervised method for image recognition

mixupfamily icon mixupfamily

The implementation of mixup and mainfold mixup method with standard models(PreActRes, WideRes, Dense) in Cifar10, Cifar100 and SVHN dataset on supervised(sl) and semi-supervised(ssl) tasks.

moco icon moco

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

moco-pytorch icon moco-pytorch

An unofficial Pytorch implementation of "Improved Baselines with Momentum Contrastive Learning" (MoCoV2) - X. Chen, et al.

moco-v3 icon moco-v3

PyTorch implementation of MoCo v3 https//arxiv.org/abs/2104.02057

models icon models

Models and examples built with TensorFlow

noisy_label icon noisy_label

Code for the CVPR15 paper "Learning from Massive Noisy Labeled Data for Image Classification"

pba icon pba

Efficient Learning of Augmentation Policy Schedules

pytorch-cifar100 icon pytorch-cifar100

Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet, NasNet, Residual Attention Network, SENet)

pytorch-playground icon pytorch-playground

Base pretrained models and datasets in pytorch (MNIST, SVHN, CIFAR10, CIFAR100, STL10, AlexNet, VGG16, VGG19, ResNet, Inception, SqueezeNet)

readme icon readme

README文件语法解读,即Github Flavored Markdown语法介绍

swav icon swav

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

tensorboardx icon tensorboardx

tensorboard for pytorch (and chainer, mxnet, numpy, ...)

uda icon uda

TensorFlow code for Unsupervised Data Augmentation (UDA)

unsup_temp_embed icon unsup_temp_embed

Official implementation of the paper: Unsupervised learning of action classes with continuous temporal embedding (CVPR'19)

vat icon vat

Code for reproducing the results on the MNIST dataset in the paper "Distributional Smoothing with Virtual Adversarial Training"

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