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cifar
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resnet
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206 search results found
Trained Rank Pruning
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35
Pytorch implementation of TRP
Wide Residual Network
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35
Wide-residual network implementations. Best result for cifar10(97.12%), cifar100(84.12%), and other kaggle challenges
Lp_bnn
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34
This repository contains an official implementation of LPBNN.
Dynamic Routing Capsule Cifar
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33
CapsNet reference from : https://github.com/XifengGuo/CapsNet-Keras
Pytorch Nn Practice
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33
💩 My pytorch neural network practice repo
Sharesnet
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32
ShaResNet: reducing residual network parameter number by sharing weights
Checkered Cnn
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28
A new technique to increase receptive field in convolutional neural networks without losing so much information.
Adabatch
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27
AdaBatch: Adaptive Batch Sizes for Training Deep Neural Networks
Deep Compression.pytorch
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26
Unofficial Pytorch implementation of Deep Compression in CIFAR10
Esnac
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25
Learnable Embedding Space for Efficient Neural Architecture Compression
L Dnq
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25
Codes for AAAI2019 paper: Deep Neural Network Quantization via Layer-Wise Optimization using Limited Training Data
Cnn Models
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25
YOLO-v2, ResNet-32, GoogLeNet-lite
Residual Flow
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25
An implementation of the Residual Flow algorithm for out-of-distribution detection.
Power Iteration Svd
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24
Backpropagation-Friendly-Eigendecomposition
Tensorbag
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24
Collection of tensorflow notebooks tutorials for implementing the most important Deep Learning algorithms.
Resnet
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22
An implementation of the original "ResNet" paper in Pytorch
Pytorch Template
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20
A template for PyTorch projects.
Hold Me Tight
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19
Source code of "Hold me tight! Influence of discriminative features on deep network boundaries"
Keras Cifar10
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19
practice on CIFAR10 with Keras
Wide_residual_nets_caffe
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19
training wide residual networks in caffe
Patternrecognitionanddeeplearning Lab
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19
2019春哈工大模式识别与深度学习实验
Frequency Response Characterization Of Cnns
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18
Pruningneuralnetworks
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18
This repository provides the implementation of the method proposed in our paper "Pruning Deep Neural Networks using Partial Least Squares"
Epsilonresnet
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17
The implementation of epsilon ResNet
Cifarclassify
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17
实现常用图像分类算法
Bam Cbam Pytorch
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17
Pytorch implementation of BAM("BAM: Bottleneck Attention Module", BMVC18) and CBAM(“CBAM: Convolutional Block Attention Module”, ECCV18)
Push Pull Cnn Layer
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17
PyTorch implementation of the PushPull layer for CNNs.
Caffe Wrn Generator
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17
Caffe Wide-Residual-Network (WRN) Generator
Resnet Pytorch Cifar10
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16
PyTorch implementation of residual networks trained on CIFAR-10 dataset
Fdg
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16
Fully Decoupled Neural Network Learning Using Delayed Gradients (FDG)
Pytorch Examples
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16
PyTorch examples for NERSC systems
Distributed Resnet Tensorflow
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15
A Distributed ResNet on multi-machines each with one GPU card.
Search The Number Of Channels
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15
Cnn
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14
pytorch implementation of several CNNs for image classification
Matconvnet Resnet
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14
MatConvNet Implementation for Deep Residual Networks
Cifar Tensorflow
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14
Sc19 Dl Tutorial
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14
Hands-on material for the SC19 tutorial, Deep Learning at Scale
Lookahead_pytorch
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13
Pytorch implementation of lookahead optimizer(https://arxiv.org/pdf/1907.08610.pdf) and RAdam(https://arxiv.org/pdf/1908.03265.pdf)
Gdfq
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13
official implementation of Generative Low-bitwidth Data Free Quantization(GDFQ)
Temperature Scaling Tensorflow
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13
On Calibration of Modern Neural Networks - tensorflow implementation
Cifar 10_resnet_tensorflow
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13
resnet Identity Mappings in tensorflow
Cnns_for_classifing_cifar10
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13
An implement of LeNet, AlexNet, VGG16, GoogLeNet and ResNet with Tensorflow.
Adversarial Explanations Cifar
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13
Code example for the paper, "Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness."
Caffe Project Vggnet Resnet Densenet
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13
Pmf
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12
Proximal Mean-field for Neural Network Quantization
Iternorm Pytorch
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12
This is the pytorch re-implementation of the IterNorm
Simsiam
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12
Exploring Simple Siamese Representation Learning
Label_smoothing_pytorch
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11
pytorch implement of Label Smoothing
Pytorch Cifar
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11
Self realization CNN CIFAR-10
Zam
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11
ZAM: Zero parameter Attention Module
Epruning
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11
Energy-based Dropout and Pruning of Deep Neural Networks
Peernets Pytorch
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11
A pytorch implementation of 'PeerNets: Exploiting Peer Wisdom Against Adversarial Attacks'
Resnet_cifar10_cifar100_imagenet
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11
resnet_cifar10_cifar100_imagenet
Pytorch Static Quantization
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10
PyTorch Static Quantization Example
Resnet Brelu
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10
ResNet and DenseNet with Bipolar Rectified Linear Units (BReLU)
Tf2 Evonorm
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9
TensorFlow 2.0 implementation of Evonorm
Pytorch Quant
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9
DL quantization for pytorch
Matconvnet Resnet
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9
Deep Residual Networks for MatConvNet
Branchynet_chainer
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9
基于提前退出部分样本原理而实现的带分支网络(supported by chainer)
Vanilla Adversarial Training
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8
vanilla training and adversarial training in PyTorch
Ttp Neuralnets Compression
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8
We implement an efficient mechanism for compressing large networks by {\em tensorizing\/} network layers: i.e. mapping layers on to high-order matrices, for which we introduce new tensor decomposition methods.
Flowandprune
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8
Codebase for the paper "A Gradient Flow Framework for Analyzing Network Pruning"
Pytorch Cinic 10
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8
Pytorch deep learning object detection using CINIC-10 dataset.
Pytorch Quantization Aware Training
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8
PyTorch Quantization Aware Training Example
Hands On Deep Learning Using Tensorflow 2.0
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8
重读 CNN 网络的经典论文,并用 tensorflow 2.0 手撸一遍经典模型,感受一下实测数据
Dnn Gating
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8
Res Se Net
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8
Boosting performance of Resnets by enhancing bridge-connections
Sc18 Dl Tutorial
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8
Keras tutorial code for the SC18 tutorial on Deep Learning at Scale
Cnn Gpu Benchmarks
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8
Latest (2020) CNN and GPU Benchmarks on ImageNet and CIFAR
Shake Shake Keras
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8
Keras implementation of Shake-Shake regularization
Ood Detection
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7
Code for "Zero-Shot Out-of-Distribution Detection with Feature Correlations"
Classification Cifar10 Pytorch
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7
Train several classical classification networks in cifar10 dataset by PyTorch
Multi Sample_dropout_pytorch
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7
a simple pytorch implement of Multi-Sample Dropout
Resnet Pytorch
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7
Cifar10 Resnet Tensorflow
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7
base backbone model
Cnn_models_comparation.pytorch
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7
Traditional Convolution Neural Networks (CNN) Comparation
Pytorch_simple_classification_baselines
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7
Simple pytorch classification baselines for MNIST, CIFAR and ImageNet
Torch Tresnet
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7
Packaged TResNet based on Official PyTorch Implementation
Ternarized_neural_network
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6
Optimizing Deep Convolutional Neural Network with Ternarized Weights and High Accuracy
Cifar_pytorch Lightning
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6
CIFAR10, CIFAR100 results with VGG16,Resnet50,WideResnet using pytorch-lightning
Cifar10 Faster
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6
[WIP] Demonstration of training a small ResNet on CIFAR10 to 94% test accuracy in less 20 epochs
Paddle Cifar100
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6
paddle cifar100 training
Gradient Secure
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6
Cifar10_pytorch
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6
Model benchmark on CIFAR10 dataset in PyTorch.
Gconv Prune
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6
Code repository for paper "Efficient Structured Pruning and Architecture Searching for Group Convolution" https://arxiv.org/abs/1811.09341
Pytorch Cifar10
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6
practice on CIFAR10 with PyTorch
Dnn_sharpest_directions
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6
Code for "On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length", ICLR 2019
Uniformaugment
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6
Unofficial PyTorch Reimplementation of UniformAugment.
Svb
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6
Code release for the CVPR2017 paper "Improving training of deep neural networks via Singular Value Bounding". Achieving error rates of 3.06% on CIFAR-10 and 16.90% on CIFAR-100.
Keras Alchemy
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6
keras alchemy trick
Resnet Tensorflow
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6
ResNet in tensorflow for CIFAR-100, CIFAR-10
Senet Tensorflow
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6
Simple Tensorflow implementation of Squeeze Excitation Networks (ResNeXt, Inception-v4, Inception-resnet-v2). Include focal loss, center loss.
Htd
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5
Source code for HTD (WACV 2019)
Fs Neurons
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5
Try Wide Residual Net
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5
A simple Wide ResNet implementation with Keras.
Classification_uncertainty
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5
Focal_calibration
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5
Code for the paper "Calibrating Deep Neural Networks using Focal Loss"
Cnn Cifar10
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5
Implement and Compare VGG, ResNet and ResNeXt on CIFAR-10
Stochasticity_in_neural_ode
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5
"Stochasticity in Neural ODEs: An Empirical Study". Experiments from the paper
Pytorch_cls
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5
A classification repo implemented with PyTorch on CIFAR-10 and ImageNet under different training conditions
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