cifar10

Classification with PyTorch.

A PyTorch implementation for exploring deep and shallow knowledge distillation (KD) experiments with flexibility

PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet

Play deep learning with CIFAR datasets

A coding-free framework built on PyTorch for reproducible deep learning studies. 🏆20 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.

Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

[ICCV 2019] "AutoGAN: Neural Architecture Search for Generative Adversarial Networks" by Xinyu Gong, Shiyu Chang, Yifan Jiang and Zhangyang Wang

A PyTorch implementation of SimCLR based on ICML 2020 paper "A Simple Framework for Contrastive Learning of Visual Representations"

Pretrained TorchVision models on CIFAR10 dataset (with weights)

3.41% and 17.11% error on CIFAR-10 and CIFAR-100

Naszilla is a Python library for neural architecture search (NAS)

DAWNBench: An End-to-End Deep Learning Benchmark and Competition

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

Non-negative Positive-Unlabeled (nnPU) and unbiased Positive-Unlabeled (uPU) learning reproductive code on MNIST and CIFAR10

Bottleneck Transformers for Visual Recognition

ResNet-20/32/44/56/110 on CIFAR-10 with Caffe

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

pytorch implement of Lookahead Optimizer

Speech commands recognition with PyTorch | Kaggle 10th place solution in TensorFlow Speech Recognition Challenge

Personalized federated learning simulation platform with Non-IID and unbalanced dataset

Various CNN models for CIFAR10 with Chainer

Code for CVPR 2019 paper: " Learning Deep Compositional Grammatical Architectures for Visual Recognition"

Reimplementation ResNet on cifar10 with caffe

Pytorch implementation of Virtual Adversarial Training

Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search

Spectral Normalization for Keras Dense and Convolution Layers

Pretrained models on CIFAR10/100 in PyTorch

A PyTorch implementation of shake-shake