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The Wayback Machine - https://web.archive.org/web/20200918084720/https://github.com/topics/dropout
Here are
153 public repositories
matching this topic...
Build your neural network easy and fast
Updated
Jun 8, 2020
Jupyter Notebook
Tensorflow tutorial from basic to hard
Updated
Aug 5, 2020
Python
Satania IS the BEST waifu, no really, she is, if you don't believe me, this website will convince you
Updated
Jul 30, 2020
HTML
Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.
Updated
Jul 29, 2020
Python
🔬 Nano size Theano LSTM module
Updated
Nov 16, 2016
Python
Implementations of CNNs, RNNs and deep learning techniques in pure Numpy
Updated
May 16, 2020
Python
Complementary code for the Targeted Dropout paper
Updated
Sep 26, 2019
Python
MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.
Updated
Jul 26, 2018
Python
Artificial Intelligence Learning Notes.
Updated
Jan 28, 2020
Python
repo that holds code for improving on dropout using Stochastic Delta Rule
Updated
Feb 10, 2019
Python
Updated
Dec 29, 2019
Python
PyTorch implementations of LSTM Variants (Dropout + Layer Norm)
Updated
Mar 29, 2019
Python
Implementation of DropBlock in Pytorch
Updated
Nov 4, 2018
Python
AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.
Updated
Feb 27, 2020
Python
Single (i) Cell R package (iCellR) is an interactive R package to work with high-throughput single cell sequencing technologies (i.e scRNA-seq, scVDJ-seq and CITE-seq).
PyTorch Implementations of Dropout Variants
Updated
Jan 7, 2018
Jupyter Notebook
Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.
Updated
May 2, 2018
Python
The tools and syntax you need to code neural networks from day one.
Updated
Sep 25, 2017
Jupyter Notebook
My workshop on machine learning using python language to implement different algorithms
Updated
Jan 24, 2020
Jupyter Notebook
Google Street View House Number(SVHN) Dataset, and classifying them through CNN
Updated
Mar 4, 2018
Jupyter Notebook
Implementation of key concepts of neuralnetwork via numpy
Updated
Feb 6, 2018
Python
Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch
Updated
Nov 3, 2017
Python
Bayesian Neural Network in PyTorch
Updated
Sep 14, 2019
Python
Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019
Updated
Jan 31, 2020
Python
Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.
Updated
Aug 16, 2020
Python
Imputation method for scRNA-seq based on low-rank approximation
Updated
Mar 30, 2020
Jupyter Notebook
Understanding nuts and bolts of neural networks with PyTorch
Win probability predictions for League of Legends matches using neural networks
Updated
Jul 18, 2020
Python
DropBlock implemented in Keras
Updated
May 17, 2020
Python
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