24 Open source projects that are alternatives of or similar to Variance Networks

Satania IS the BEST waifu, no really, she is, if you don't believe me, this website will convince you

Implementation of DropBlock: A regularization method for convolutional networks in PyTorch.

Tensorflow tutorial from basic to hard, 莫烦Python 中文AI教学

🔬 Nano size Theano LSTM module

Implementation of CNNs, RNNs, and many deep learning techniques in plain Numpy.

DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020

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

PyTorch Implementations of Dropout Variants

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

Selective Classification For Deep Neural Networks.

Win probability predictions for League of Legends matches using neural networks

Implementation of key concepts of neuralnetwork via numpy

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

Complementary code for the Targeted Dropout paper

Artificial Intelligence Learning Notes.

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

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

datagrand 2019 information extraction competition rank9

PyTorch implementations of LSTM Variants (Dropout + Layer Norm)

Stochastic Delta Rule implemented in Pytorch on DenseNet

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, ST and CITE-seq).

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

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

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