Play deep learning with CIFAR datasets
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Updated
Aug 27, 2020 - Python
Play deep learning with CIFAR datasets
Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"
Implementing Searching for MobileNetV3 paper using Pytorch
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
[ICLR 2024] SemiReward: A General Reward Model for Semi-supervised Learning
An implementation of MobileNetV3 with pyTorch
Collection of tensorflow notebooks tutorials for implementing some basic Deep Learning architectures.
paddle cifar100 training
Official PyTorch Implementation of Guarding Barlow Twins Against Overfitting with Mixed Samples
Selective Classification For Deep Neural Networks.
Convolutional Neural Networks using Tensorflow with Cifar-100 dataset
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