There are 4 repositories under cifar10 topic.
A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility
Classification with PyTorch.
A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆25 knowledge distillation methods presented at CVPR, ICLR, ECCV, NeurIPS, ICCV, etc are implemented so far. 🎁 Trained models, training logs and configurations are available for ensuring the reproducibiliy and benchmark.
PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet
Train to 94% on CIFAR-10 in <6.3 seconds on a single A100. Or ~95.79% in ~110 seconds (or less!)
Keras implementation of "One pixel attack for fooling deep neural networks" using differential evolution on Cifar10 and ImageNet
Play deep learning with CIFAR datasets
Pretrained TorchVision models on CIFAR10 dataset (with weights)
Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet
A PyTorch implementation of SimCLR based on ICML 2020 paper "A Simple Framework for Contrastive Learning of Visual Representations"
[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang
CAI NEURAL API - Pascal based deep learning neural network API optimized for AVX, AVX2 and AVX512 instruction sets plus OpenCL capable devices including AMD, Intel and NVIDIA.
3.41% and 17.11% error on CIFAR-10 and CIFAR-100
Pretrained models on CIFAR10/100 in PyTorch
Non-negative Positive-Unlabeled (nnPU) and unbiased Positive-Unlabeled (uPU) learning reproductive code on MNIST and CIFAR10
Bottleneck Transformers for Visual Recognition
DAWNBench: An End-to-End Deep Learning Benchmark and Competition
Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
用于pytorch的图像分类,包含多种模型方法,比如AlexNet,VGG,GoogleNet,ResNet,DenseNet等等,包含可完整运行的代码。除此之外,也有colab的在线运行代码,可以直接在colab在线运行查看结果。也可以迁移到自己的数据集进行迁移学习。
Speech commands recognition with PyTorch | Kaggle 10th place solution in TensorFlow Speech Recognition Challenge
pytorch implement of Lookahead Optimizer
ResNet-20/32/44/56/110 on CIFAR-10 with Caffe
PyTorch implementation of "Pruning Filters For Efficient ConvNets"
Various CNN models for CIFAR10 with Chainer
Reference implementation for Blueprint Separable Convolutions (CVPR 2020)
Pytorch implementation of Virtual Adversarial Training
Spectral Normalization for Keras Dense and Convolution Layers
各种深度学习结构、模型和技巧的集合
The official implementation of the ACM MM'21 paper Co-learning: Learning from noisy labels with self-supervision.
[CVPR 2021] Code for "Augmentation Strategies for Learning with Noisy Labels".
A PyTorch implementation of "EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks".