CIFAR10 PyTorch implementation of "MixMatch - A Holistic Approach to Semi-Supervised Learning"
-
Updated
Nov 27, 2023 - Python
CIFAR10 PyTorch implementation of "MixMatch - A Holistic Approach to Semi-Supervised Learning"
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, WideResNet)
An implementation of WideResNets with Fixup initialization in Jax/Flax. This can be useful for use cases where Batch Normalization should be avoided (for example when using the Laplace approximation to the Bayesian posterior).
PyTorch implementation of deep CNNs
Code for paper: "Improved Residual Network Based on Norm-Preservation for Visual Recognition" https://doi.org/10.1016/j.neunet.2022.10.023
PyTorch implementation for 3D CNN models for medical image data (1 channel gray scale images).
vanilla training and adversarial training in PyTorch
Image recognition on CIFAR 10, CIFAR 100, Caltech 101 and Caltech 256 datasets. With the implementation of WideResNet, InceptionV3 and DenseNet neural networks.
Wide Residual Networks (WideResNets) in PyTorch
CIFAR10, CIFAR100 results with VGG16,Resnet50,WideResnet using pytorch-lightning
WideResNet implementation on MNIST dataset. FGSM and PGD adversarial attacks on standard training, PGD adversarial training, and Feature Scattering adversarial training.
SE-Net Incorporates with ResNet and WideResnet on CIFAR-10/100 Dataset.
Add a description, image, and links to the wideresnet topic page so that developers can more easily learn about it.
To associate your repository with the wideresnet topic, visit your repo's landing page and select "manage topics."