There are 2 repositories under cifar-100 topic.
Play deep learning with CIFAR datasets
Implementing Searching for MobileNetV3 paper using Pytorch
Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
A PyTorch implementation for PyramidNets (Deep Pyramidal Residual Networks, https://arxiv.org/abs/1610.02915)
ResNet with Shift, Depthwise, or Convolutional Operations for CIFAR-100, CIFAR-10 on PyTorch
Torch implementation of the paper "Deep Pyramidal Residual Networks" (https://arxiv.org/abs/1610.02915).
Code for the neural architecture search methods contained in the paper Efficient Forward Neural Architecture Search
Multi-task learning for image classification implemented in PyTorch.
Implementing Randomly Wired Neural Networks for Image Recognition, Using CIFAR-10 dataset, CIFAR-100 dataset
This is the PyTorch-0.4.0 implementation of few-shot learning on CIFAR-100 with graph neural networks (GNN)
sensAI: ConvNets Decomposition via Class Parallelism for Fast Inference on Live Data
An implementation of MobileNetV3 with pyTorch
[ICLR 2024] SemiReward: A General Reward Model for Semi-supervised Learning
Collection of tensorflow notebooks tutorials for implementing some basic Deep Learning architectures.
paddle cifar100 training
Selective Classification For Deep Neural Networks.
Convolutional Neural Networks using Tensorflow with Cifar-100 dataset
Residual Network Experiments with CIFAR Datasets.
VGG models from ILSVRC 2014
A PyTorch framework for federated learning. This is a very basic framework.
We implement NNCLR and a novel clustering-based technique for contrastive learning that we call KMCLR. We show that applying a clustering technique to obtain prototype embeddings and using these prototypes to form positive pairs for contrastive loss can achieve performances on par with NNCLR on CIFAR-100 while storing 0.4% of the number of vectors.
Official code for "PubDef: Defending Against Transfer Attacks From Public Models" (ICLR 2024)
Plug-and-play collaboration between specialized Tsetlin machines
This repository provides experiment results for MobileNetV2 based on PyTorch.
Wide-Resnet-Ensemble implementation for CIFAR100 kaggle submission: >83.97% on kaggle private leaderboard
Transfer Learning to Classify CIFAR-100 images
The repository contains the codebase for Relative Weight Change in layers of Deep Neural Networks.
Object classification on CIFAR-100 dataset using VGG-NET. [Validation Accuracy 70.48%]
A deeper look into dense shortcut nets.
ISEF 2023 (TEAM CANADA) PROJECT. Find the complete documentation and code in the README file linked here and below.
Image recognition on CIFAR 10, CIFAR 100, Caltech 101 and Caltech 256 datasets. With the implementation of WideResNet, InceptionV3 and DenseNet neural networks.