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MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

tensorflow cnn dropout mnist batch-normalization mnist-classification data-augmentation ensemble-prediction

Updated Jul 26, 2018
Python

noahfl / densenet-sdr

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repo that holds code for improving on dropout using Stochastic Delta Rule

statistics deep-neural-networks deep-learning neural-network dropout

Updated Feb 10, 2019
Python

lonePatient / daguan_2019_rank9

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datagrand 2019 information extraction competition rank9

crf pytorch information-extraction lstm dropout ie ngram span ner bert lookahead train-bert

Updated Dec 29, 2019
Python

seba-1511 / lstms.pth

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PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

pytorch lstm dropout moon rnn gal

Updated May 7, 2021
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, scATAC-seq, CITE-Seq and Spatial Transcriptomics (ST)).

clustering dropout batch-normalization imputation scrna-seq diffusion-maps clustering-algorithm 3d umap normalization 10xgenomics cell-type-classification intractive-graph cite-seq singel-cell-sequencing pseudotime scvdj-seq icellr

Updated Jun 9, 2021
R

Randl / DropBlock-pytorch

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Implementation of DropBlock in Pytorch

pytorch dropout pytorch-implementation dropblock

Updated Nov 4, 2018
Python

snrazavi / Machine-Learning-in-Python-Workshop

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My workshop on machine learning using python language to implement different algorithms

python machine-learning workshop deep-learning numpy scikit-learn keras dropout batch-normalization neural-networks matplotlib convolutional-neural-networks gradient-descent backpropagation optimization-algorithms softmax machine-learning-workshop linear-classification

Updated Jan 24, 2020
Jupyter Notebook

thtrieu / essence

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AutoDiff DAG constructor, built on numpy and Cython. A Neural Turing Machine and DeepQ agent run on it. Clean code for educational purpose.

machine-learning reinforcement-learning deep-learning recurrent-neural-networks lstm dropout mnist neural-turing-machines question-answering cartpole lstm-model lenet convolutional-networks convolutional-neural-networks deep-q-network computational-graphs auto-differentiation

Updated Feb 27, 2020
Python

j-min / Dropouts

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PyTorch Implementations of Dropout Variants

pytorch dropout variational-inference bayesian-neural-networks local-reparametrization-trick gaussian-dropout variational-dropout

Updated Jan 7, 2018
Jupyter Notebook

ivannz / cplxmodule

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Complex-valued neural networks for pytorch and Variational Dropout for real and complex layers.

pytorch dropout complex-networks variational-bayes sparsification

Updated Jul 29, 2021
Python

ahmedfgad / CIFAR10CNNFlask

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Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.

javascript css python html http flask computer-vision tensorflow convnet image-processing cnn web-application dropout image-classification convolutional-neural-network fully-connected-network max-pooling relu

Updated May 2, 2018
Python

emilwallner / Deep-Learning-101

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The tools and syntax you need to code neural networks from day one.

machine-learning deep-learning dropout regularization tflearn

Updated Sep 25, 2017
Jupyter Notebook

aditya9211 / SVHN-CNN

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Google Street View House Number(SVHN) Dataset, and classifying them through CNN

machine-learning computer-vision cnn dropout mnist svhn convolutional-neural-networks confusion-matrix google-street convolutional-neural-network tensorboard-visualizations tesnorflow svhn-classifier grayscale-images house-numbers adam-optimizer mini-batch-gradient-descent one-hot-encode

Updated Mar 4, 2018
Jupyter Notebook

hwalsuklee / numpy-neuralnet-exercise

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Implementation of key concepts of neuralnetwork via numpy

neural-network numpy cnn dropout mnist sgd regularization deeplearning xavier-initializer relu cross-entropy-loss numpy-neuralnet-exercise

Updated Feb 6, 2018
Python

anassinator / bnn

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Bayesian Neural Network in PyTorch

neural-network pytorch artificial-intelligence dropout bayesian-inference bayesian-neural-networks bnn concrete-dropout

Updated Sep 14, 2019
Python

georgezoto / TensorFlow-in-Practice

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TensorFlow in Practice Specialization. Join our Deep Learning Adventures community 🎉 and become an expert in Deep Learning, TensorFlow, Computer Vision, Convolutional Neural Networks, Kaggle Challenges, Data Augmentation and Dropouts Transfer Learning, Multiclass Classifications and Overfitting and Natural Language Processing NLP as well as Time Series Forecasting 😀 All while having fun learning and participating in our Deep Learning Trivia games 🎉 http://bit.ly/deep-learning-tf

natural-language-processing computer-vision deep-learning tensorflow kaggle dropout neural-networks convolutional-neural-networks data-augmentation multiclass-classification trivia-game overfitting timeseries-forecasting tensorflow-developer-certificate

Updated Jul 10, 2020
Jupyter Notebook

kefirski / variational_dropout

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Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch

python machine-learning neural-network paper pytorch dropout bayesian-inference posterior-probability local-reparametrization-trick

Updated Nov 3, 2017
Python

da-molchanov / variance-networks

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Variance Networks: When Expectation Does Not Meet Your Expectations, ICLR 2019

deep-learning dropout variance-networks iclr2019

Updated Jan 31, 2020
Python

fahadm / Bayesian-Active-Learning-Pytorch

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Implementation of Bayesian NNs in Pytorch (https://arxiv.org/pdf/1703.02910.pdf) (With some help from https://github.com/Riashat/Deep-Bayesian-Active-Learning/))

machine-learning neural-network pytorch dropout bayesian-networks active-learning

Updated Jun 8, 2021
Jupyter Notebook

KlugerLab / ALRA

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Imputation method for scRNA-seq based on low-rank approximation

dropout imputation scrna-seq svd matrix-completion

Updated Jan 13, 2021
R

minihat / LoL-Match-Prediction

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Win probability predictions for League of Legends matches using neural networks

big-data neural-network league-of-legends video-game artificial-intelligence dropout batch-normalization match-prediction

Updated Jul 18, 2020
Python

srinadhu / CS231n

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My solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition

Updated Sep 5, 2018
Jupyter Notebook

dropout

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MorvanZhou / PyTorch-Tutorial

MorvanZhou / Tensorflow-Tutorial

Pizzacus / satania.moe

miguelvr / dropblock

JonathanRaiman / theano_lstm

parasdahal / deepnet

for-ai / Targeted-Dropout

Jackpopc / aiLearnNotes

hwalsuklee / tensorflow-mnist-cnn

noahfl / densenet-sdr

lonePatient / daguan_2019_rank9

seba-1511 / lstms.pth

rezakj / iCellR

Randl / DropBlock-pytorch

snrazavi / Machine-Learning-in-Python-Workshop

thtrieu / essence

j-min / Dropouts

ivannz / cplxmodule

ahmedfgad / CIFAR10CNNFlask

emilwallner / Deep-Learning-101

aditya9211 / SVHN-CNN

hwalsuklee / numpy-neuralnet-exercise

anassinator / bnn

georgezoto / TensorFlow-in-Practice

kefirski / variational_dropout

da-molchanov / variance-networks

fahadm / Bayesian-Active-Learning-Pytorch

KlugerLab / ALRA

minihat / LoL-Match-Prediction

srinadhu / CS231n

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