batch-normalization
There are 204 repositories under batch-normalization topic.
MorvanZhou/PyTorch-Tutorial
Build your neural network easy and fast, 莫烦Python中文教学
cvjena/cnn-models
ImageNet pre-trained models with batch normalization for the Caffe framework
anish-lakkapragada/SeaLion
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
parasdahal/deepnet
Deep learning library in plain Numpy.
AdalbertoCq/Deep-Learning-Specialization-Coursera
Deep Learning Specialization courses by Andrew Ng, deeplearning.ai
twke18/Adaptive_Affinity_Fields
Adaptive Affinity Fields for Semantic Segmentation
tamakoji/pytorch-syncbn
Synchronized Multi-GPU Batch Normalization
hwalsuklee/tensorflow-mnist-cnn
MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.
imedslab/pytorch_bn_fusion
Batch normalization fusion for PyTorch. This is an archived repository, which is not maintained.
rezakj/iCellR
iCellR is an interactive R package designed to facilitate the analysis and visualization of high-throughput single-cell sequencing data. It supports a variety of single-cell technologies, including scRNA-seq, scVDJ-seq, scATAC-seq, CITE-Seq, and Spatial Transcriptomics (ST).
snrazavi/Machine-Learning-in-Python-Workshop
My workshop on machine learning using python language to implement different algorithms
lyttonhao/Neural-Style-MMD
MXNet Code For Demystifying Neural Style Transfer (IJCAI 2017)
adityab/CrossQ
Official code release for "CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity"
mkeid/Feed-Forward-Style-Transfer
TensorFlow implementation of real-time style transfer using feed-forward generation. This builds on the original style-transfer algorithm and allows for common personal computers to transform images.
stevenobadja/math_object_detection
An image recognition/object detection model that detects handwritten digits and simple math operators. The output of the predicted objects (numbers & math operators) is then evaluated and solved.
soloice/mnist-bn
Using slim to perform batch normalization
VITA-Group/BNN_NoBN
[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang
hwalsuklee/tensorflow-mnist-MLP-batch_normalization-weight_initializers
MNIST classification using Multi-Layer Perceptron (MLP) with 2 hidden layers. Some weight-initializers and batch-normalization are implemented.
VITA-Group/Sandwich-Batch-Normalization
[WACV 2022] "Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity" by Xinyu Gong, Wuyang Chen, Tianlong Chen and Zhangyang Wang
minihat/LoL-Match-Prediction
Win probability predictions for League of Legends matches using neural networks
shantanu1109/Coursera-DeepLearning.AI-GANs-Specialization
This Repository Contains Solution to the Assignments of the Generative Adversarial Networks (GANs) Specialization from deeplearning.ai on Coursera Taught by Sharon Zhou, Eda Zhou, Eric Zelikman
AdityaDutt/Audio-Classification-Using-Wavelet-Transform
Classifying audio using Wavelet transform and deep learning
26hzhang/AmusingPythonCodes
Interesting python codes to tackle simple machine/deep learning tasks
knsong/caffe-mt
This is a fork of caffe added some useful layers, the original caffe site is https://github.com/BVLC/caffe.
bobye/batchnorm_prune
Tensorflow codes for "Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolution Layers"
Cyril9227/Keras_AttentiveNormalization
Unofficial Keras implementation of the paper Attentive Normalization.
sayakpaul/Training-BatchNorm-and-Only-BatchNorm
Experiments with the ideas presented in https://arxiv.org/abs/2003.00152 by Frankle et al.
ayansengupta17/GAN
We aim to generate realistic images from text descriptions using GAN architecture. The network that we have designed is used for image generation for two datasets: MSCOCO and CUBS.
AdityaDutt/Bird-Song-Classification
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.
xternalz/SDPoint
Stochastic Downsampling for Cost-Adjustable Inference and Improved Regularization in Convolutional Networks
apple/ml-tune-mode-convbn
Tune-Mode ConvBN Blocks For Efficient Transfer Learning
SSQ/Coursera-Ng-Improving-Deep-Neural-Networks-Hyperparameter-tuning-Regularization-and-Optimization
Short description for quick search
AdalbertoCq/NeuralNetwork
Neural Network implementation in Numpy and Keras. Batch Normalization, Dropout, L2 Regularization and Optimizers
shiranzada/pure-noise
Official implementation for "Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images" https://arxiv.org/abs/2112.08810
eigenfoo/batch-renorm
A Tensorflow re-implementation of batch renormalization, first introduced by Sergey Ioffe.
osu-cvl/revisiting-bn-init
Code for "Revisiting Batch Norm Initialization".